├── Fountain ├── K562 │ ├── K562_WT_totalS_fountains_100kb_bs.bedpe │ ├── K562_WT_totalS_fountains_10kb_bs.bedpe │ ├── K562_WT_totalS_fountains_200kb_bs.bedpe │ ├── K562_WT_totalS_fountains_20kb_bs.bedpe │ ├── K562_WT_totalS_fountains_50kb_bs.bedpe │ └── K562_WT_totalS_fountains_5kb_bs.bedpe └── mESC │ ├── mES_WT_totalS_100kb_bs.bedpe │ ├── mES_WT_totalS_10kb_bs.bedpe │ ├── mES_WT_totalS_200kb_bs.bedpe │ ├── mES_WT_totalS_20kb_bs.bedpe │ ├── mES_WT_totalS_50kb_bs.bedpe │ └── mES_WT_totalS_5kb_bs.bedpe ├── Fun ├── LICENSE ├── README.md ├── __pycache__ ├── __init__.cpython-38.pyc └── __main__.cpython-38.pyc ├── cli ├── __init__.py ├── __pycache__ │ ├── __init__.cpython-38.pyc │ ├── calculate_SoN.cpython-38.pyc │ ├── calculate_extension_infor.cpython-38.pyc │ ├── find_summits.cpython-38.pyc │ ├── measure_strength.cpython-38.pyc │ └── test.cpython-38.pyc ├── calculate_SoN.py ├── calculate_extension_infor.py └── find_summits.py ├── image ├── .DS_Store ├── Fountains.png └── Fun.png └── lib ├── __init__.py ├── __pycache__ ├── __init__.cpython-38.pyc ├── diagonal_plumb.cpython-38.pyc ├── find_peaks.cpython-38.pyc ├── fountain_extension.cpython-38.pyc ├── generate_summits.cpython-38.pyc ├── ks_test.cpython-38.pyc ├── merge_fountains.cpython-38.pyc ├── quality_filter.cpython-38.pyc ├── rotation.cpython-38.pyc ├── signal_over_noise.cpython-38.pyc ├── test.cpython-38.pyc ├── trans_to_bedpe.cpython-38.pyc └── util.cpython-38.pyc ├── diagonal_plumb.py ├── find_peaks.py ├── fountain_extension.py ├── generate_summits.py ├── ks_test.py ├── merge_fountains.py ├── quality_filter.py ├── rotation.py ├── signal_over_noise.py ├── trans_to_bedpe.py └── util.py /Fountain/K562/K562_WT_totalS_fountains_100kb_bs.bedpe: -------------------------------------------------------------------------------- 1 | <<<<<<< HEAD 2 | version https://git-lfs.github.com/spec/v1 3 | oid sha256:a0804c1b96505cc10862ad9c7835daca884ac77e7e0025d8072334f620d59ff7 4 | size 18363 5 | ======= 6 | chr1 x1 x2 chr2 y1 y2 7 | chr1 26550000 26650000 chr1 29150000 29250000 8 | chr1 14950000 15050000 chr1 17750000 17850000 9 | chr1 17450000 17550000 chr1 19450000 19550000 10 | chr1 29550000 29650000 chr1 31150000 31250000 11 | chr1 38950000 39050000 chr1 42550000 42650000 12 | chr1 47050000 47150000 chr1 52250000 52350000 13 | chr1 33050000 33150000 chr1 36250000 36350000 14 | chr1 23750000 23850000 chr1 26750000 26850000 15 | chr1 67750000 67850000 chr1 71150000 71250000 16 | chr1 75950000 76050000 chr1 78550000 78650000 17 | chr1 60550000 60650000 chr1 62550000 62650000 18 | chr1 3250000 3350000 chr1 6850000 6950000 19 | chr1 115050000 115150000 chr1 117050000 117150000 20 | chr1 116750000 116850000 chr1 118550000 118650000 21 | chr1 151550000 151650000 chr1 153750000 153850000 22 | chr1 156650000 156750000 chr1 160850000 160950000 23 | chr1 159350000 159450000 chr1 162950000 163050000 24 | chr1 145850000 145950000 chr1 147650000 147750000 25 | chr1 173050000 173150000 chr1 174650000 174750000 26 | chr1 163050000 163150000 chr1 165250000 165350000 27 | chr1 193050000 193150000 chr1 196450000 196550000 28 | chr1 197650000 197750000 chr1 201250000 201350000 29 | chr1 209450000 209550000 chr1 215450000 215550000 30 | chr1 215350000 215450000 chr1 218150000 218250000 31 | chr1 220550000 220650000 chr1 223350000 223450000 32 | chr1 224450000 224550000 chr1 226250000 226350000 33 | chr1 231650000 231750000 chr1 234250000 234350000 34 | chr1 233050000 233150000 chr1 237850000 237950000 35 | chr1 244350000 244450000 chr1 247550000 247650000 36 | chr10 6750000 6850000 chr10 11750000 11850000 37 | chr10 15450000 15550000 chr10 17250000 17350000 38 | chr10 21050000 21150000 chr10 23850000 23950000 39 | chr10 23350000 23450000 chr10 24950000 25050000 40 | chr10 24950000 25050000 chr10 27150000 27250000 41 | chr10 36250000 36350000 chr10 38050000 38150000 42 | chr10 34550000 34650000 chr10 36150000 36250000 43 | chr10 52650000 52750000 chr10 60050000 60150000 44 | chr10 98750000 98850000 chr10 102750000 102850000 45 | chr10 65550000 65650000 chr10 69750000 69850000 46 | chr10 77250000 77350000 chr10 79050000 79150000 47 | chr10 82650000 82750000 chr10 85650000 85750000 48 | chr10 94550000 94650000 chr10 97550000 97650000 49 | chr10 88150000 88250000 chr10 89750000 89850000 50 | chr10 106150000 106250000 chr10 108950000 109050000 51 | chr10 108950000 109050000 chr10 111150000 111250000 52 | chr10 111350000 111450000 chr10 113350000 113450000 53 | chr10 116150000 116250000 chr10 118550000 118650000 54 | chr10 120350000 120450000 chr10 121950000 122050000 55 | chr10 127250000 127350000 chr10 130450000 130550000 56 | chr11 850000 950000 chr11 3450000 3550000 57 | chr11 14750000 14850000 chr11 16950000 17050000 58 | chr11 20750000 20850000 chr11 22350000 22450000 59 | chr11 22150000 22250000 chr11 27750000 27850000 60 | chr11 25550000 25650000 chr11 29550000 29650000 61 | chr11 26950000 27050000 chr11 32350000 32450000 62 | chr11 48150000 48250000 chr11 50150000 50250000 63 | chr11 16550000 16650000 chr11 19150000 19250000 64 | chr11 78450000 78550000 chr11 82450000 82550000 65 | chr11 82850000 82950000 chr11 85650000 85750000 66 | chr11 90250000 90350000 chr11 92850000 92950000 67 | chr11 96050000 96150000 chr11 98050000 98150000 68 | chr11 106850000 106950000 chr11 109450000 109550000 69 | chr11 111250000 111350000 chr11 114450000 114550000 70 | chr11 113950000 114050000 chr11 116750000 116850000 71 | chr11 120250000 120350000 chr11 122650000 122750000 72 | chr11 126350000 126450000 chr11 129350000 129450000 73 | chr11 127450000 127550000 chr11 132450000 132550000 74 | chr11 130250000 130350000 chr11 134450000 134550000 75 | chr12 6450000 6550000 chr12 8450000 8550000 76 | chr12 16650000 16750000 chr12 18250000 18350000 77 | chr12 18350000 18450000 chr12 22750000 22850000 78 | chr12 41950000 42050000 chr12 44550000 44650000 79 | chr12 56250000 56350000 chr12 58050000 58150000 80 | chr12 58750000 58850000 chr12 62550000 62650000 81 | chr12 62650000 62750000 chr12 65250000 65350000 82 | chr12 31050000 31150000 chr12 33050000 33150000 83 | chr12 105050000 105150000 chr12 108450000 108550000 84 | chr12 96750000 96850000 chr12 98750000 98850000 85 | chr12 80350000 80450000 chr12 83550000 83650000 86 | chr12 86250000 86350000 chr12 88650000 88750000 87 | chr12 75450000 75550000 chr12 77650000 77750000 88 | chr12 97450000 97550000 chr12 103850000 103950000 89 | chr12 108450000 108550000 chr12 114650000 114750000 90 | chr12 113950000 114050000 chr12 117150000 117250000 91 | chr12 117250000 117350000 chr12 120850000 120950000 92 | chr13 33950000 34050000 chr13 36950000 37050000 93 | chr13 40650000 40750000 chr13 43450000 43550000 94 | chr13 42350000 42450000 chr13 45350000 45450000 95 | chr13 45950000 46050000 chr13 50150000 50250000 96 | chr13 62650000 62750000 chr13 64250000 64350000 97 | chr13 50350000 50450000 chr13 52150000 52250000 98 | chr13 111650000 111750000 chr13 113450000 113550000 99 | chr14 20550000 20650000 chr14 22350000 22450000 100 | chr14 23050000 23150000 chr14 25250000 25350000 101 | chr14 49750000 49850000 chr14 51550000 51650000 102 | chr14 53450000 53550000 chr14 55050000 55150000 103 | chr14 55550000 55650000 chr14 58750000 58850000 104 | chr14 61750000 61850000 chr14 64550000 64650000 105 | chr14 69850000 69950000 chr14 73650000 73750000 106 | chr14 78850000 78950000 chr14 81450000 81550000 107 | chr14 82250000 82350000 chr14 88650000 88750000 108 | chr14 97450000 97550000 chr14 99650000 99750000 109 | chr14 100050000 100150000 chr14 106450000 106550000 110 | chr15 49950000 50050000 chr15 52750000 52850000 111 | chr15 53150000 53250000 chr15 55350000 55450000 112 | chr15 45750000 45850000 chr15 48950000 49050000 113 | chr15 85550000 85650000 chr15 89550000 89650000 114 | chr15 76250000 76350000 chr15 77850000 77950000 115 | chr15 72750000 72850000 chr15 74350000 74450000 116 | chr15 88650000 88750000 chr15 92250000 92350000 117 | chr16 16750000 16850000 chr16 18550000 18650000 118 | chr16 12050000 12150000 chr16 14650000 14750000 119 | chr16 4850000 4950000 chr16 8650000 8750000 120 | chr16 27450000 27550000 chr16 31850000 31950000 121 | chr16 25150000 25250000 chr16 27550000 27650000 122 | chr16 51050000 51150000 chr16 52850000 52950000 123 | chr16 53550000 53650000 chr16 55950000 56050000 124 | chr16 72350000 72450000 chr16 74150000 74250000 125 | chr16 55750000 55850000 chr16 59350000 59450000 126 | chr16 81650000 81750000 chr16 84250000 84350000 127 | chr17 9250000 9350000 chr17 13450000 13550000 128 | chr17 5050000 5150000 chr17 6850000 6950000 129 | chr17 6250000 6350000 chr17 9050000 9150000 130 | chr17 16750000 16850000 chr17 18350000 18450000 131 | chr17 76650000 76750000 chr17 79050000 79150000 132 | chr17 49850000 49950000 chr17 53050000 53150000 133 | chr17 42750000 42850000 chr17 45950000 46050000 134 | chr17 38350000 38450000 chr17 40150000 40250000 135 | chr17 58350000 58450000 chr17 60150000 60250000 136 | chr17 34550000 34650000 chr17 36350000 36450000 137 | chr17 62150000 62250000 chr17 65750000 65850000 138 | chr17 67850000 67950000 chr17 70250000 70350000 139 | chr18 11450000 11550000 chr18 13450000 13550000 140 | chr18 8950000 9050000 chr18 12350000 12450000 141 | chr18 32150000 32250000 chr18 34750000 34850000 142 | chr18 29850000 29950000 chr18 32250000 32350000 143 | chr18 27950000 28050000 chr18 30550000 30650000 144 | chr18 35050000 35150000 chr18 37050000 37150000 145 | chr18 650000 750000 chr18 2650000 2750000 146 | chr18 22950000 23050000 chr18 29750000 29850000 147 | chr18 43650000 43750000 chr18 46450000 46550000 148 | chr18 49250000 49350000 chr18 51250000 51350000 149 | chr18 57050000 57150000 chr18 60050000 60150000 150 | chr18 59050000 59150000 chr18 61850000 61950000 151 | chr18 74350000 74450000 chr18 77150000 77250000 152 | chr18 72150000 72250000 chr18 74550000 74650000 153 | chr18 67550000 67650000 chr18 72150000 72250000 154 | chr19 8350000 8450000 chr19 10550000 10650000 155 | chr19 1850000 1950000 chr19 3450000 3550000 156 | chr19 30650000 30750000 chr19 32850000 32950000 157 | chr19 35250000 35350000 chr19 40050000 40150000 158 | chr19 42950000 43050000 chr19 45550000 45650000 159 | chr19 56750000 56850000 chr19 58550000 58650000 160 | chr2 3650000 3750000 chr2 7050000 7150000 161 | chr2 8550000 8650000 chr2 12950000 13050000 162 | chr2 16550000 16650000 chr2 20950000 21050000 163 | chr2 19250000 19350000 chr2 21850000 21950000 164 | chr2 20850000 20950000 chr2 24050000 24150000 165 | chr2 12650000 12750000 chr2 15450000 15550000 166 | chr2 25350000 25450000 chr2 28750000 28850000 167 | chr2 33550000 33650000 chr2 36950000 37050000 168 | chr2 38550000 38650000 chr2 43550000 43650000 169 | chr2 127250000 127350000 chr2 129650000 129750000 170 | chr2 56450000 56550000 chr2 58050000 58150000 171 | chr2 96350000 96450000 chr2 98350000 98450000 172 | chr2 62550000 62650000 chr2 64550000 64650000 173 | chr2 64250000 64350000 chr2 66250000 66350000 174 | chr2 65750000 65850000 chr2 68350000 68450000 175 | chr2 69750000 69850000 chr2 75150000 75250000 176 | chr2 73250000 73350000 chr2 75450000 75550000 177 | chr2 75450000 75550000 chr2 80250000 80350000 178 | chr2 103450000 103550000 chr2 105450000 105550000 179 | chr2 105850000 105950000 chr2 109650000 109750000 180 | chr2 122850000 122950000 chr2 127450000 127550000 181 | chr2 41850000 41950000 chr2 48450000 48550000 182 | chr2 131750000 131850000 chr2 135950000 136050000 183 | chr2 134250000 134350000 chr2 137850000 137950000 184 | chr2 136750000 136850000 chr2 139150000 139250000 185 | chr2 155750000 155850000 chr2 158350000 158450000 186 | chr2 146450000 146550000 chr2 149250000 149350000 187 | chr2 148550000 148650000 chr2 150350000 150450000 188 | chr2 149850000 149950000 chr2 152250000 152350000 189 | chr2 153350000 153450000 chr2 156950000 157050000 190 | chr2 183550000 183650000 chr2 187750000 187850000 191 | chr2 198850000 198950000 chr2 201050000 201150000 192 | chr2 192650000 192750000 chr2 196650000 196750000 193 | chr2 211250000 211350000 chr2 213650000 213750000 194 | chr2 214050000 214150000 chr2 216050000 216150000 195 | chr2 218450000 218550000 chr2 221050000 221150000 196 | chr2 220850000 220950000 chr2 223250000 223350000 197 | chr2 225350000 225450000 chr2 228150000 228250000 198 | chr2 228350000 228450000 chr2 230950000 231050000 199 | chr2 233750000 233850000 chr2 236950000 237050000 200 | chr2 233450000 233550000 chr2 239650000 239750000 201 | chr20 11250000 11350000 chr20 15650000 15750000 202 | chr20 650000 750000 chr20 3250000 3350000 203 | chr20 13950000 14050000 chr20 16750000 16850000 204 | chr20 23450000 23550000 chr20 25250000 25350000 205 | chr20 16950000 17050000 chr20 19150000 19250000 206 | chr20 52450000 52550000 chr20 55450000 55550000 207 | chr20 46950000 47050000 chr20 50350000 50450000 208 | chr20 37450000 37550000 chr20 39650000 39750000 209 | chr20 39950000 40050000 chr20 42350000 42450000 210 | chr20 50050000 50150000 chr20 52050000 52150000 211 | chr20 55050000 55150000 chr20 58250000 58350000 212 | chr20 58050000 58150000 chr20 60050000 60150000 213 | chr21 41050000 41150000 chr21 43250000 43350000 214 | chr22 31350000 31450000 chr22 37350000 37450000 215 | chr22 29150000 29250000 chr22 32750000 32850000 216 | chr22 46650000 46750000 chr22 50650000 50750000 217 | chr22 38350000 38450000 chr22 42150000 42250000 218 | chr3 102150000 102250000 chr3 105350000 105450000 219 | chr3 27950000 28050000 chr3 30150000 30250000 220 | chr3 4350000 4450000 chr3 10350000 10450000 221 | chr3 9950000 10050000 chr3 13150000 13250000 222 | chr3 20250000 20350000 chr3 24050000 24150000 223 | chr3 34050000 34150000 chr3 36850000 36950000 224 | chr3 52950000 53050000 chr3 57750000 57850000 225 | chr3 56150000 56250000 chr3 59350000 59450000 226 | chr3 62150000 62250000 chr3 64150000 64250000 227 | chr3 71350000 71450000 chr3 73350000 73450000 228 | chr3 31850000 31950000 chr3 34250000 34350000 229 | chr3 99250000 99350000 chr3 101850000 101950000 230 | chr3 94250000 94350000 chr3 97050000 97150000 231 | chr3 113850000 113950000 chr3 115450000 115550000 232 | chr3 125250000 125350000 chr3 127650000 127750000 233 | chr3 138450000 138550000 chr3 141650000 141750000 234 | chr3 143150000 143250000 chr3 145750000 145850000 235 | chr3 146350000 146450000 chr3 148950000 149050000 236 | chr3 160850000 160950000 chr3 163850000 163950000 237 | chr3 152150000 152250000 chr3 155350000 155450000 238 | chr3 172750000 172850000 chr3 176550000 176650000 239 | chr3 164150000 164250000 chr3 167350000 167450000 240 | chr3 179350000 179450000 chr3 182350000 182450000 241 | chr4 13350000 13450000 chr4 15750000 15850000 242 | chr4 10450000 10550000 chr4 13250000 13350000 243 | chr4 30550000 30650000 chr4 33350000 33450000 244 | chr4 32050000 32150000 chr4 37250000 37350000 245 | chr4 36850000 36950000 chr4 42450000 42550000 246 | chr4 42750000 42850000 chr4 44350000 44450000 247 | chr4 91250000 91350000 chr4 94850000 94950000 248 | chr4 61750000 61850000 chr4 64150000 64250000 249 | chr4 93950000 94050000 chr4 97350000 97450000 250 | chr4 95550000 95650000 chr4 99750000 99850000 251 | chr4 164250000 164350000 chr4 166050000 166150000 252 | chr4 166650000 166750000 chr4 169450000 169550000 253 | chr4 104250000 104350000 chr4 106450000 106550000 254 | chr4 106750000 106850000 chr4 108950000 109050000 255 | chr4 119950000 120050000 chr4 122950000 123050000 256 | chr4 134850000 134950000 chr4 139450000 139550000 257 | chr4 141350000 141450000 chr4 144550000 144650000 258 | chr4 168350000 168450000 chr4 172350000 172450000 259 | chr4 155850000 155950000 chr4 159050000 159150000 260 | chr4 170150000 170250000 chr4 174150000 174250000 261 | chr4 183250000 183350000 chr4 187250000 187350000 262 | chr5 1950000 2050000 chr5 6150000 6250000 263 | chr5 8650000 8750000 chr5 12250000 12350000 264 | chr5 11250000 11350000 chr5 14450000 14550000 265 | chr5 29250000 29350000 chr5 31250000 31350000 266 | chr5 31850000 31950000 chr5 35250000 35350000 267 | chr5 34750000 34850000 chr5 36750000 36850000 268 | chr5 40650000 40750000 chr5 43250000 43350000 269 | chr5 61550000 61650000 chr5 64950000 65050000 270 | chr5 65250000 65350000 chr5 68050000 68150000 271 | chr5 142250000 142350000 chr5 145250000 145350000 272 | chr5 89750000 89850000 chr5 95150000 95250000 273 | chr5 98150000 98250000 chr5 102350000 102450000 274 | chr5 111450000 111550000 chr5 119250000 119350000 275 | chr5 114650000 114750000 chr5 119050000 119150000 276 | chr5 151250000 151350000 chr5 153650000 153750000 277 | chr5 155950000 156050000 chr5 160550000 160650000 278 | chr5 130350000 130450000 chr5 135550000 135650000 279 | chr5 132950000 133050000 chr5 135350000 135450000 280 | chr5 134650000 134750000 chr5 137450000 137550000 281 | chr5 137450000 137550000 chr5 139650000 139750000 282 | chr5 145850000 145950000 chr5 148050000 148150000 283 | chr5 151550000 151650000 chr5 156550000 156650000 284 | chr5 147750000 147850000 chr5 151750000 151850000 285 | chr5 154750000 154850000 chr5 156550000 156650000 286 | chr5 164350000 164450000 chr5 167550000 167650000 287 | chr5 169850000 169950000 chr5 171450000 171550000 288 | chr5 159250000 159350000 chr5 163450000 163550000 289 | chr5 175550000 175650000 chr5 177350000 177450000 290 | chr5 172850000 172950000 chr5 175850000 175950000 291 | chr6 13350000 13450000 chr6 16150000 16250000 292 | chr6 8050000 8150000 chr6 10450000 10550000 293 | chr6 45150000 45250000 chr6 47150000 47250000 294 | chr6 47450000 47550000 chr6 49650000 49750000 295 | chr6 53450000 53550000 chr6 56650000 56750000 296 | chr6 70850000 70950000 chr6 74250000 74350000 297 | chr6 76450000 76550000 chr6 79850000 79950000 298 | chr6 78650000 78750000 chr6 82050000 82150000 299 | chr6 64550000 64650000 chr6 67950000 68050000 300 | chr6 80850000 80950000 chr6 82850000 82950000 301 | chr6 83950000 84050000 chr6 86550000 86650000 302 | chr6 97450000 97550000 chr6 99650000 99750000 303 | chr6 100250000 100350000 chr6 105250000 105350000 304 | chr6 116850000 116950000 chr6 119250000 119350000 305 | chr6 110550000 110650000 chr6 112550000 112650000 306 | chr6 146550000 146650000 chr6 148150000 148250000 307 | chr6 147550000 147650000 chr6 149750000 149850000 308 | chr6 161250000 161350000 chr6 167250000 167350000 309 | chr6 148950000 149050000 chr6 152150000 152250000 310 | chr6 155450000 155550000 chr6 157050000 157150000 311 | chr6 164450000 164550000 chr6 166250000 166350000 312 | chr7 12650000 12750000 chr7 17050000 17150000 313 | chr7 2650000 2750000 chr7 5050000 5150000 314 | chr7 9050000 9150000 chr7 10650000 10750000 315 | chr7 27750000 27850000 chr7 29550000 29650000 316 | chr7 29350000 29450000 chr7 31350000 31450000 317 | chr7 30950000 31050000 chr7 32550000 32650000 318 | chr7 33950000 34050000 chr7 38350000 38450000 319 | chr7 47650000 47750000 chr7 50050000 50150000 320 | chr7 53950000 54050000 chr7 57550000 57650000 321 | chr7 51650000 51750000 chr7 55450000 55550000 322 | chr7 63650000 63750000 chr7 67450000 67550000 323 | chr7 67350000 67450000 chr7 69750000 69850000 324 | chr7 73650000 73750000 chr7 75650000 75750000 325 | chr7 78050000 78150000 chr7 80650000 80750000 326 | chr7 4950000 5050000 chr7 6950000 7050000 327 | chr7 91150000 91250000 chr7 92950000 93050000 328 | chr7 95650000 95750000 chr7 97450000 97550000 329 | chr7 112650000 112750000 chr7 116250000 116350000 330 | chr7 105050000 105150000 chr7 106650000 106750000 331 | chr7 72750000 72850000 chr7 74350000 74450000 332 | chr7 102750000 102850000 chr7 104750000 104850000 333 | chr7 131050000 131150000 chr7 134850000 134950000 334 | chr7 135550000 135650000 chr7 137750000 137850000 335 | chr7 137550000 137650000 chr7 141350000 141450000 336 | chr7 140850000 140950000 chr7 142450000 142550000 337 | chr7 123050000 123150000 chr7 127650000 127750000 338 | chr7 152250000 152350000 chr7 155050000 155150000 339 | chr7 157050000 157150000 chr7 158650000 158750000 340 | chr7 147550000 147650000 chr7 152950000 153050000 341 | chr8 13050000 13150000 chr8 15050000 15150000 342 | chr8 2650000 2750000 chr8 6450000 6550000 343 | chr8 23150000 23250000 chr8 27150000 27250000 344 | chr8 33750000 33850000 chr8 36750000 36850000 345 | chr8 38950000 39050000 chr8 41150000 41250000 346 | chr8 49850000 49950000 chr8 53050000 53150000 347 | chr8 47850000 47950000 chr8 49450000 49550000 348 | chr8 54150000 54250000 chr8 57750000 57850000 349 | chr8 57250000 57350000 chr8 59250000 59350000 350 | chr8 59350000 59450000 chr8 61550000 61650000 351 | chr8 68950000 69050000 chr8 70750000 70850000 352 | chr8 71350000 71450000 chr8 72950000 73050000 353 | chr8 40850000 40950000 chr8 43050000 43150000 354 | chr8 92450000 92550000 chr8 94650000 94750000 355 | chr8 83150000 83250000 chr8 85750000 85850000 356 | chr8 99050000 99150000 chr8 101450000 101550000 357 | chr8 96050000 96150000 chr8 98650000 98750000 358 | chr8 99350000 99450000 chr8 106150000 106250000 359 | chr8 73450000 73550000 chr8 75650000 75750000 360 | chr8 122950000 123050000 chr8 127150000 127250000 361 | chr8 118950000 119050000 chr8 120550000 120650000 362 | chr8 128150000 128250000 chr8 131550000 131650000 363 | chr8 131850000 131950000 chr8 134050000 134150000 364 | chr8 133550000 133650000 chr8 136550000 136650000 365 | chr8 136150000 136250000 chr8 140150000 140250000 366 | chr8 140750000 140850000 chr8 142950000 143050000 367 | chr8 142050000 142150000 chr8 144450000 144550000 368 | chr8 126450000 126550000 chr8 128650000 128750000 369 | chr9 15850000 15950000 chr9 18250000 18350000 370 | chr9 97250000 97350000 chr9 99450000 99550000 371 | chr9 104650000 104750000 chr9 106850000 106950000 372 | chr9 79350000 79450000 chr9 81150000 81250000 373 | chr9 112350000 112450000 chr9 114150000 114250000 374 | chr9 119650000 119750000 chr9 122850000 122950000 375 | chr9 116950000 117050000 chr9 119550000 119650000 376 | chr9 136450000 136550000 chr9 138450000 138550000 377 | chrX 17350000 17450000 chrX 19550000 19650000 378 | chrX 23450000 23550000 chrX 25050000 25150000 379 | chrX 27950000 28050000 chrX 30550000 30650000 380 | chrX 41050000 41150000 chrX 44450000 44550000 381 | chrX 77250000 77350000 chrX 79850000 79950000 382 | chrX 64950000 65050000 chrX 68150000 68250000 383 | chrX 103150000 103250000 chrX 106350000 106450000 384 | chrX 106550000 106650000 chrX 109750000 109850000 385 | chrX 119750000 119850000 chrX 122550000 122650000 386 | chrX 124950000 125050000 chrX 128150000 128250000 387 | chrX 131450000 131550000 chrX 133250000 133350000 388 | chrX 142650000 142750000 chrX 144450000 144550000 389 | >>>>>>> fd3f9c132494aa3a0536aa90e5f7d71514f59a00 390 | -------------------------------------------------------------------------------- /Fountain/K562/K562_WT_totalS_fountains_200kb_bs.bedpe: -------------------------------------------------------------------------------- 1 | <<<<<<< HEAD 2 | version https://git-lfs.github.com/spec/v1 3 | oid sha256:d3ae194c9aeb8605a8847086ca45c7dfd9951b095ea484e4f001a3a6cb28e4ca 4 | size 11026 5 | ======= 6 | chr1 x1 x2 chr2 y1 y2 7 | chr1 28700000 28900000 chr1 31900000 32100000 8 | chr1 11900000 12100000 chr1 16300000 16500000 9 | chr1 17500000 17700000 chr1 21100000 21300000 10 | chr1 51100000 51300000 chr1 55900000 56100000 11 | chr1 32300000 32500000 chr1 36700000 36900000 12 | chr1 36100000 36300000 chr1 40900000 41100000 13 | chr1 39300000 39500000 chr1 46500000 46700000 14 | chr1 79100000 79300000 chr1 84300000 84500000 15 | chr1 71900000 72100000 chr1 75100000 75300000 16 | chr1 47500000 47700000 chr1 51900000 52100000 17 | chr1 93900000 94100000 chr1 101100000 101300000 18 | chr1 101300000 101500000 chr1 109700000 109900000 19 | chr1 144300000 144500000 chr1 148300000 148500000 20 | chr1 186500000 186700000 chr1 192100000 192300000 21 | chr1 149900000 150100000 chr1 156300000 156500000 22 | chr1 174900000 175100000 chr1 178900000 179100000 23 | chr1 149900000 150100000 chr1 161500000 161700000 24 | chr1 160100000 160300000 chr1 168500000 168700000 25 | chr1 192500000 192700000 chr1 196900000 197100000 26 | chr1 208100000 208300000 chr1 211700000 211900000 27 | chr1 209900000 210100000 chr1 215100000 215300000 28 | chr1 214100000 214300000 chr1 219300000 219500000 29 | chr1 237700000 237900000 chr1 240900000 241100000 30 | chr1 220700000 220900000 chr1 223900000 224100000 31 | chr10 18300000 18500000 chr10 21500000 21700000 32 | chr10 53700000 53900000 chr10 59700000 59900000 33 | chr10 6100000 6300000 chr10 12100000 12300000 34 | chr10 88900000 89100000 chr10 94100000 94300000 35 | chr10 79300000 79500000 chr10 82900000 83100000 36 | chr10 94700000 94900000 chr10 98700000 98900000 37 | chr10 118100000 118300000 chr10 128900000 129100000 38 | chr10 115300000 115500000 chr10 118900000 119100000 39 | chr11 23300000 23500000 chr11 26500000 26700000 40 | chr11 8100000 8300000 chr11 13700000 13900000 41 | chr11 31900000 32100000 chr11 37100000 37300000 42 | chr11 41700000 41900000 chr11 50500000 50700000 43 | chr11 27900000 28100000 chr11 31500000 31700000 44 | chr11 12100000 12300000 chr11 17700000 17900000 45 | chr11 67500000 67700000 chr11 72300000 72500000 46 | chr11 82500000 82700000 chr11 86100000 86300000 47 | chr11 116500000 116700000 chr11 120500000 120700000 48 | chr11 103100000 103300000 chr11 106300000 106500000 49 | chr11 125700000 125900000 chr11 129700000 129900000 50 | chr11 126900000 127100000 chr11 133300000 133500000 51 | chr12 1300000 1500000 chr12 7300000 7500000 52 | chr12 22300000 22500000 chr12 25500000 25700000 53 | chr12 25300000 25500000 chr12 33700000 33900000 54 | chr12 49900000 50100000 chr12 53900000 54100000 55 | chr12 53700000 53900000 chr12 57300000 57500000 56 | chr12 92300000 92500000 chr12 96300000 96500000 57 | chr12 125100000 125300000 chr12 132300000 132500000 58 | chr12 71900000 72100000 chr12 76300000 76500000 59 | chr12 114100000 114300000 chr12 117300000 117500000 60 | chr12 107100000 107300000 chr12 115500000 115700000 61 | chr13 53300000 53500000 chr13 59700000 59900000 62 | chr13 46300000 46500000 chr13 49500000 49700000 63 | chr14 31700000 31900000 chr14 35300000 35500000 64 | chr14 24300000 24500000 chr14 31100000 31300000 65 | chr14 45700000 45900000 chr14 50100000 50300000 66 | chr14 50700000 50900000 chr14 55500000 55700000 67 | chr14 20500000 20700000 chr14 25300000 25500000 68 | chr14 74300000 74500000 chr14 77900000 78100000 69 | chr14 82500000 82700000 chr14 88500000 88700000 70 | chr14 89500000 89700000 chr14 94300000 94500000 71 | chr14 101300000 101500000 chr14 106100000 106300000 72 | chr15 23900000 24100000 chr15 27900000 28100000 73 | chr15 28100000 28300000 chr15 35300000 35500000 74 | chr15 44300000 44500000 chr15 51100000 51300000 75 | chr15 40700000 40900000 chr15 45100000 45300000 76 | chr15 52500000 52700000 chr15 56500000 56700000 77 | chr15 35500000 35700000 chr15 39100000 39300000 78 | chr15 68100000 68300000 chr15 74100000 74300000 79 | chr15 94700000 94900000 chr15 99100000 99300000 80 | chr15 59700000 59900000 chr15 73300000 73500000 81 | chr15 89700000 89900000 chr15 93700000 93900000 82 | chr16 11900000 12100000 chr16 15100000 15300000 83 | chr16 21500000 21700000 chr16 29900000 30100000 84 | chr16 26500000 26700000 chr16 32900000 33100000 85 | chr16 58100000 58300000 chr16 66900000 67100000 86 | chr16 67100000 67300000 chr16 70700000 70900000 87 | chr16 85500000 85700000 chr16 89100000 89300000 88 | chr17 26700000 26900000 chr17 38300000 38500000 89 | chr17 26700000 26900000 chr17 31100000 31300000 90 | chr17 53500000 53700000 chr17 60300000 60500000 91 | chr17 49500000 49700000 chr17 53900000 54100000 92 | chr17 66500000 66700000 chr17 71300000 71500000 93 | chr17 73100000 73300000 chr17 76300000 76500000 94 | chr18 8500000 8700000 chr18 13300000 13500000 95 | chr18 24300000 24500000 chr18 28700000 28900000 96 | chr18 28500000 28700000 chr18 34100000 34300000 97 | chr18 3900000 4100000 chr18 8700000 8900000 98 | chr18 55900000 56100000 chr18 60700000 60900000 99 | chr18 60300000 60500000 chr18 67900000 68100000 100 | chr18 68100000 68300000 chr18 71700000 71900000 101 | chr18 40900000 41100000 chr18 50100000 50300000 102 | chr19 14300000 14500000 chr19 17900000 18100000 103 | chr19 39500000 39700000 chr19 42700000 42900000 104 | chr19 41900000 42100000 chr19 45900000 46100000 105 | chr19 29900000 30100000 chr19 33500000 33700000 106 | chr2 16300000 16500000 chr2 20700000 20900000 107 | chr2 24300000 24500000 chr2 29500000 29700000 108 | chr2 33500000 33700000 chr2 37100000 37300000 109 | chr2 38900000 39100000 chr2 43300000 43500000 110 | chr2 132100000 132300000 chr2 135700000 135900000 111 | chr2 42500000 42700000 chr2 47700000 47900000 112 | chr2 48100000 48300000 chr2 54900000 55100000 113 | chr2 68700000 68900000 chr2 75500000 75700000 114 | chr2 76300000 76500000 chr2 79500000 79700000 115 | chr2 114100000 114300000 chr2 128100000 128300000 116 | chr2 121300000 121500000 chr2 128900000 129100000 117 | chr2 114500000 114700000 chr2 119700000 119900000 118 | chr2 144300000 144500000 chr2 147500000 147700000 119 | chr2 153300000 153500000 chr2 156900000 157100000 120 | chr2 154900000 155100000 chr2 164100000 164300000 121 | chr2 188500000 188700000 chr2 200500000 200700000 122 | chr2 216900000 217100000 chr2 220500000 220700000 123 | chr2 234100000 234300000 chr2 238500000 238700000 124 | chr20 17700000 17900000 chr20 23300000 23500000 125 | chr20 9900000 10100000 chr20 13100000 13300000 126 | chr20 30900000 31100000 chr20 36500000 36700000 127 | chr20 42300000 42500000 chr20 50300000 50500000 128 | chr20 56100000 56300000 chr20 61300000 61500000 129 | chr21 38500000 38700000 chr21 44900000 45100000 130 | chr21 33500000 33700000 chr21 39900000 40100000 131 | chr22 30300000 30500000 chr22 37900000 38100000 132 | chr22 36500000 36700000 chr22 43700000 43900000 133 | chr3 94900000 95100000 chr3 104500000 104700000 134 | chr3 1100000 1300000 chr3 7500000 7700000 135 | chr3 24100000 24300000 chr3 33300000 33500000 136 | chr3 31700000 31900000 chr3 39300000 39500000 137 | chr3 38500000 38700000 chr3 42900000 43100000 138 | chr3 53500000 53700000 chr3 57100000 57300000 139 | chr3 81700000 81900000 chr3 87300000 87500000 140 | chr3 48900000 49100000 chr3 52500000 52700000 141 | chr3 107100000 107300000 chr3 113100000 113300000 142 | chr3 100700000 100900000 chr3 107500000 107700000 143 | chr3 182100000 182300000 chr3 186900000 187100000 144 | chr3 183300000 183500000 chr3 196900000 197100000 145 | chr4 90700000 90900000 chr4 95500000 95700000 146 | chr4 32700000 32900000 chr4 36700000 36900000 147 | chr4 23500000 23700000 chr4 27500000 27700000 148 | chr4 25900000 26100000 chr4 33100000 33300000 149 | chr4 26100000 26300000 chr4 38100000 38300000 150 | chr4 82100000 82300000 chr4 90100000 90300000 151 | chr4 35500000 35700000 chr4 43500000 43700000 152 | chr4 169500000 169700000 chr4 175100000 175300000 153 | chr4 95900000 96100000 chr4 99500000 99700000 154 | chr4 114500000 114700000 chr4 119300000 119500000 155 | chr4 123500000 123700000 chr4 129100000 129300000 156 | chr4 119900000 120100000 chr4 123100000 123300000 157 | chr4 127500000 127700000 chr4 141500000 141700000 158 | chr4 130300000 130500000 chr4 133900000 134100000 159 | chr4 155900000 156100000 chr4 159100000 159300000 160 | chr4 179300000 179500000 chr4 182500000 182700000 161 | chr4 182900000 183100000 chr4 188100000 188300000 162 | chr4 92100000 92300000 chr4 98900000 99100000 163 | chr5 1500000 1700000 chr5 6300000 6500000 164 | chr5 13100000 13300000 chr5 17900000 18100000 165 | chr5 38100000 38300000 chr5 43300000 43500000 166 | chr5 55700000 55900000 chr5 60900000 61100000 167 | chr5 60500000 60700000 chr5 65700000 65900000 168 | chr5 90500000 90700000 chr5 102500000 102700000 169 | chr5 111500000 111700000 chr5 119100000 119300000 170 | chr5 130100000 130300000 chr5 135300000 135500000 171 | chr5 103500000 103700000 chr5 107100000 107300000 172 | chr5 127100000 127300000 chr5 130300000 130500000 173 | chr5 147900000 148100000 chr5 151500000 151700000 174 | chr5 159300000 159500000 chr5 163300000 163500000 175 | chr5 133300000 133500000 chr5 138900000 139100000 176 | chr5 163900000 164100000 chr5 168300000 168500000 177 | chr5 172700000 172900000 chr5 175900000 176100000 178 | chr5 98100000 98300000 chr5 102100000 102300000 179 | chr6 21300000 21500000 chr6 24500000 24700000 180 | chr6 3100000 3300000 chr6 7500000 7700000 181 | chr6 1300000 1500000 chr6 5700000 5900000 182 | chr6 12700000 12900000 chr6 16700000 16900000 183 | chr6 39900000 40100000 chr6 46300000 46500000 184 | chr6 36900000 37100000 chr6 42900000 43100000 185 | chr6 76500000 76700000 chr6 79700000 79900000 186 | chr6 119300000 119500000 chr6 122900000 123100000 187 | chr6 126100000 126300000 chr6 130900000 131100000 188 | chr6 161300000 161500000 chr6 167700000 167900000 189 | chr6 138900000 139100000 chr6 143300000 143500000 190 | chr7 12300000 12500000 chr7 17100000 17300000 191 | chr7 8100000 8300000 chr7 12100000 12300000 192 | chr7 17700000 17900000 chr7 21300000 21500000 193 | chr7 66900000 67100000 chr7 71300000 71500000 194 | chr7 49900000 50100000 chr7 56700000 56900000 195 | chr7 41900000 42100000 chr7 47100000 47300000 196 | chr7 39700000 39900000 chr7 42900000 43100000 197 | chr7 35900000 36100000 chr7 39900000 40100000 198 | chr7 1100000 1300000 chr7 6300000 6500000 199 | chr7 116900000 117100000 chr7 120500000 120700000 200 | chr7 108100000 108300000 chr7 111700000 111900000 201 | chr7 70700000 70900000 chr7 77500000 77700000 202 | chr7 83100000 83300000 chr7 95100000 95300000 203 | chr7 112700000 112900000 chr7 115900000 116100000 204 | chr7 102100000 102300000 chr7 105700000 105900000 205 | chr7 151700000 151900000 chr7 155700000 155900000 206 | chr7 144100000 144300000 chr7 147700000 147900000 207 | chr7 137500000 137700000 chr7 141500000 141700000 208 | chr8 22500000 22700000 chr8 27700000 27900000 209 | chr8 18700000 18900000 chr8 25900000 26100000 210 | chr8 6500000 6700000 chr8 13300000 13500000 211 | chr8 25300000 25500000 chr8 32500000 32700000 212 | chr8 37500000 37700000 chr8 42700000 42900000 213 | chr8 62500000 62700000 chr8 66100000 66300000 214 | chr8 63700000 63900000 chr8 70500000 70700000 215 | chr8 66500000 66700000 chr8 75300000 75500000 216 | chr8 110100000 110300000 chr8 117300000 117500000 217 | chr8 86100000 86300000 chr8 92100000 92300000 218 | chr8 81500000 81700000 chr8 87100000 87300000 219 | chr8 91700000 91900000 chr8 95300000 95500000 220 | chr8 133300000 133500000 chr8 136500000 136700000 221 | chr8 135100000 135300000 chr8 140700000 140900000 222 | chr8 75700000 75900000 chr8 80100000 80300000 223 | chr9 14700000 14900000 chr9 19500000 19700000 224 | chr9 27900000 28100000 chr9 31900000 32100000 225 | chr9 81500000 81700000 chr9 85500000 85700000 226 | chr9 6500000 6700000 chr9 14500000 14700000 227 | chr9 107500000 107700000 chr9 112300000 112500000 228 | chr9 104300000 104500000 chr9 107500000 107700000 229 | chr9 94900000 95100000 chr9 101300000 101500000 230 | chrX 4100000 4300000 chrX 8900000 9100000 231 | chrX 9100000 9300000 chrX 18700000 18900000 232 | chrX 38300000 38500000 chrX 41900000 42100000 233 | chrX 88100000 88300000 chrX 92500000 92700000 234 | chrX 95900000 96100000 chrX 99900000 100100000 235 | chrX 115500000 115700000 chrX 121100000 121300000 236 | chrX 123100000 123300000 chrX 129900000 130100000 237 | >>>>>>> fd3f9c132494aa3a0536aa90e5f7d71514f59a00 238 | -------------------------------------------------------------------------------- /Fountain/K562/K562_WT_totalS_fountains_50kb_bs.bedpe: -------------------------------------------------------------------------------- 1 | <<<<<<< HEAD 2 | version https://git-lfs.github.com/spec/v1 3 | oid sha256:76851d6296c166b5f3d4436a1a1444282f3e1ce6603949db3d52ec5a9d161e77 4 | size 26316 5 | ======= 6 | chr1 x1 x2 chr2 y1 y2 7 | chr1 2225000 2275000 chr1 3425000 3475000 8 | chr1 2225000 2275000 chr1 3425000 3475000 9 | chr1 2975000 3025000 chr1 4475000 4525000 10 | chr1 4425000 4475000 chr1 5825000 5875000 11 | chr1 5775000 5825000 chr1 7275000 7325000 12 | chr1 6825000 6875000 chr1 7825000 7875000 13 | chr1 17675000 17725000 chr1 19075000 19125000 14 | chr1 33725000 33775000 chr1 35525000 35575000 15 | chr1 36525000 36575000 chr1 38425000 38475000 16 | chr1 38275000 38325000 chr1 39575000 39625000 17 | chr1 41425000 41475000 chr1 43425000 43475000 18 | chr1 48275000 48325000 chr1 50975000 51025000 19 | chr1 55925000 55975000 chr1 57125000 57175000 20 | chr1 61175000 61225000 chr1 62075000 62125000 21 | chr1 64975000 65025000 chr1 66475000 66525000 22 | chr1 68075000 68125000 chr1 70875000 70925000 23 | chr1 75475000 75525000 chr1 76775000 76825000 24 | chr1 76325000 76375000 chr1 77825000 77875000 25 | chr1 85875000 85925000 chr1 86875000 86925000 26 | chr1 87625000 87675000 chr1 89125000 89175000 27 | chr1 100275000 100325000 chr1 101075000 101125000 28 | chr1 118325000 118375000 chr1 120525000 120575000 29 | chr1 150175000 150225000 chr1 151075000 151125000 30 | chr1 151125000 151175000 chr1 154125000 154175000 31 | chr1 154275000 154325000 chr1 155075000 155125000 32 | chr1 155175000 155225000 chr1 156075000 156125000 33 | chr1 158225000 158275000 chr1 159025000 159075000 34 | chr1 162675000 162725000 chr1 165475000 165525000 35 | chr1 166025000 166075000 chr1 166925000 166975000 36 | chr1 170075000 170125000 chr1 171075000 171125000 37 | chr1 173375000 173425000 chr1 174375000 174425000 38 | chr1 176775000 176825000 chr1 177975000 178025000 39 | chr1 181125000 181175000 chr1 182125000 182175000 40 | chr1 183675000 183725000 chr1 184675000 184725000 41 | chr1 198825000 198875000 chr1 200225000 200275000 42 | chr1 208775000 208825000 chr1 209775000 209825000 43 | chr1 210925000 210975000 chr1 213825000 213875000 44 | chr1 223575000 223625000 chr1 225075000 225125000 45 | chr1 224125000 224175000 chr1 226325000 226375000 46 | chr1 232075000 232125000 chr1 233375000 233425000 47 | chr1 241525000 241575000 chr1 242325000 242375000 48 | chr1 241875000 241925000 chr1 243375000 243425000 49 | chr10 1375000 1425000 chr10 2875000 2925000 50 | chr10 475000 525000 chr10 1675000 1725000 51 | chr10 6625000 6675000 chr10 7725000 7775000 52 | chr10 11325000 11375000 chr10 12425000 12475000 53 | chr10 12825000 12875000 chr10 13925000 13975000 54 | chr10 13425000 13475000 chr10 15025000 15075000 55 | chr10 15375000 15425000 chr10 17475000 17525000 56 | chr10 23275000 23325000 chr10 25075000 25125000 57 | chr10 18625000 18675000 chr10 20025000 20075000 58 | chr10 24375000 24425000 chr10 25875000 25925000 59 | chr10 25175000 25225000 chr10 26875000 26925000 60 | chr10 27675000 27725000 chr10 28575000 28625000 61 | chr10 29775000 29825000 chr10 31775000 31825000 62 | chr10 30625000 30675000 chr10 32425000 32475000 63 | chr10 34525000 34575000 chr10 36225000 36275000 64 | chr10 37875000 37925000 chr10 38775000 38825000 65 | chr10 43925000 43975000 chr10 45925000 45975000 66 | chr10 60075000 60125000 chr10 61775000 61825000 67 | chr10 70975000 71025000 chr10 72275000 72325000 68 | chr10 70525000 70575000 chr10 74025000 74075000 69 | chr10 75075000 75125000 chr10 75975000 76025000 70 | chr10 79175000 79225000 chr10 80275000 80325000 71 | chr10 86175000 86225000 chr10 88175000 88225000 72 | chr10 87525000 87575000 chr10 90325000 90375000 73 | chr10 89375000 89425000 chr10 91275000 91325000 74 | chr10 93525000 93575000 chr10 95325000 95375000 75 | chr10 91675000 91725000 chr10 92475000 92525000 76 | chr10 99975000 100025000 chr10 101275000 101325000 77 | chr10 106375000 106425000 chr10 108775000 108825000 78 | chr10 108225000 108275000 chr10 109425000 109475000 79 | chr10 110975000 111025000 chr10 113575000 113625000 80 | chr10 113125000 113175000 chr10 113925000 113975000 81 | chr10 116725000 116775000 chr10 118225000 118275000 82 | chr10 119225000 119275000 chr10 120225000 120275000 83 | chr10 122425000 122475000 chr10 123525000 123575000 84 | chr10 128175000 128225000 chr10 129675000 129725000 85 | chr10 129825000 129875000 chr10 130925000 130975000 86 | chr11 6825000 6875000 chr11 8925000 8975000 87 | chr11 5175000 5225000 chr11 6675000 6725000 88 | chr11 4175000 4225000 chr11 6475000 6525000 89 | chr11 4075000 4125000 chr11 5175000 5225000 90 | chr11 10725000 10775000 chr11 12125000 12175000 91 | chr11 9525000 9575000 chr11 10625000 10675000 92 | chr11 13375000 13425000 chr11 14375000 14425000 93 | chr11 20725000 20775000 chr11 22625000 22675000 94 | chr11 19025000 19075000 chr11 19825000 19875000 95 | chr11 27825000 27875000 chr11 28625000 28675000 96 | chr11 31225000 31275000 chr11 32225000 32275000 97 | chr11 29325000 29375000 chr11 30225000 30275000 98 | chr11 33625000 33675000 chr11 34425000 34475000 99 | chr11 59625000 59675000 chr11 60525000 60575000 100 | chr11 59025000 59075000 chr11 59825000 59875000 101 | chr11 57525000 57575000 chr11 59325000 59375000 102 | chr11 56525000 56575000 chr11 58025000 58075000 103 | chr11 62525000 62575000 chr11 63725000 63775000 104 | chr11 108775000 108825000 chr11 109975000 110025000 105 | chr11 78575000 78625000 chr11 82275000 82325000 106 | chr11 82125000 82175000 chr11 83525000 83575000 107 | chr11 96775000 96825000 chr11 99175000 99225000 108 | chr11 96825000 96875000 chr11 97625000 97675000 109 | chr11 128475000 128525000 chr11 131375000 131425000 110 | chr11 112125000 112175000 chr11 113525000 113575000 111 | chr11 110325000 110375000 chr11 111125000 111175000 112 | chr11 107225000 107275000 chr11 109225000 109275000 113 | chr11 111125000 111175000 chr11 112425000 112475000 114 | chr11 105925000 105975000 chr11 107125000 107175000 115 | chr11 114375000 114425000 chr11 116375000 116425000 116 | chr11 122025000 122075000 chr11 123225000 123275000 117 | chr11 130575000 130625000 chr11 133975000 134025000 118 | chr12 2025000 2075000 chr12 2825000 2875000 119 | chr12 425000 475000 chr12 1825000 1875000 120 | chr12 63375000 63425000 chr12 64775000 64825000 121 | chr12 7125000 7175000 chr12 8025000 8075000 122 | chr12 3875000 3925000 chr12 4975000 5025000 123 | chr12 19625000 19675000 chr12 21425000 21475000 124 | chr12 29525000 29575000 chr12 30925000 30975000 125 | chr12 22975000 23025000 chr12 24775000 24825000 126 | chr12 25225000 25275000 chr12 26725000 26775000 127 | chr12 28025000 28075000 chr12 29225000 29275000 128 | chr12 54825000 54875000 chr12 56425000 56475000 129 | chr12 33125000 33175000 chr12 34225000 34275000 130 | chr12 55775000 55825000 chr12 58575000 58625000 131 | chr12 59525000 59575000 chr12 60325000 60375000 132 | chr12 64125000 64175000 chr12 65825000 65875000 133 | chr12 83075000 83125000 chr12 83975000 84025000 134 | chr12 89275000 89325000 chr12 90375000 90425000 135 | chr12 90325000 90375000 chr12 91625000 91675000 136 | chr12 96875000 96925000 chr12 98675000 98725000 137 | chr12 100175000 100225000 chr12 100975000 101025000 138 | chr12 113425000 113475000 chr12 114225000 114275000 139 | chr12 102225000 102275000 chr12 104325000 104375000 140 | chr12 110275000 110325000 chr12 111275000 111325000 141 | chr12 110925000 110975000 chr12 112125000 112175000 142 | chr12 111025000 111075000 chr12 113725000 113775000 143 | chr12 118675000 118725000 chr12 120175000 120225000 144 | chr12 115025000 115075000 chr12 116125000 116175000 145 | chr12 116475000 116525000 chr12 117275000 117325000 146 | chr12 124225000 124275000 chr12 125325000 125375000 147 | chr12 125975000 126025000 chr12 127475000 127525000 148 | chr12 126775000 126825000 chr12 128275000 128325000 149 | chr12 131425000 131475000 chr12 132325000 132375000 150 | chr13 22175000 22225000 chr13 23375000 23425000 151 | chr13 25875000 25925000 chr13 27575000 27625000 152 | chr13 30425000 30475000 chr13 31425000 31475000 153 | chr13 32425000 32475000 chr13 33625000 33675000 154 | chr13 42775000 42825000 chr13 44775000 44825000 155 | chr13 47075000 47125000 chr13 48675000 48725000 156 | chr13 74625000 74675000 chr13 76025000 76075000 157 | chr13 76275000 76325000 chr13 77675000 77725000 158 | chr13 95475000 95525000 chr13 96575000 96625000 159 | chr13 96525000 96575000 chr13 97725000 97775000 160 | chr13 101325000 101375000 chr13 103325000 103375000 161 | chr13 111225000 111275000 chr13 113825000 113875000 162 | chr14 21875000 21925000 chr14 23375000 23425000 163 | chr14 23075000 23125000 chr14 25175000 25225000 164 | chr14 34925000 34975000 chr14 36025000 36075000 165 | chr14 33025000 33075000 chr14 34025000 34075000 166 | chr14 33925000 33975000 chr14 34825000 34875000 167 | chr14 37775000 37825000 chr14 39575000 39625000 168 | chr14 46475000 46525000 chr14 48175000 48225000 169 | chr14 51575000 51625000 chr14 52675000 52725000 170 | chr14 52525000 52575000 chr14 53925000 53975000 171 | chr14 53825000 53875000 chr14 54725000 54775000 172 | chr14 54975000 55025000 chr14 56075000 56125000 173 | chr14 62025000 62075000 chr14 64225000 64275000 174 | chr14 68125000 68175000 chr14 69425000 69475000 175 | chr14 75775000 75825000 chr14 77375000 77425000 176 | chr14 81325000 81375000 chr14 82325000 82375000 177 | chr14 97675000 97725000 chr14 99575000 99625000 178 | chr14 85775000 85825000 chr14 86575000 86625000 179 | chr14 101325000 101375000 chr14 102225000 102275000 180 | chr14 104275000 104325000 chr14 105175000 105225000 181 | chr15 24025000 24075000 chr15 25725000 25775000 182 | chr15 25775000 25825000 chr15 27575000 27625000 183 | chr15 33925000 33975000 chr15 35725000 35775000 184 | chr15 38925000 38975000 chr15 40125000 40175000 185 | chr15 45325000 45375000 chr15 49225000 49275000 186 | chr15 61025000 61075000 chr15 62225000 62275000 187 | chr15 70725000 70775000 chr15 72325000 72375000 188 | chr15 73175000 73225000 chr15 74075000 74125000 189 | chr15 78175000 78225000 chr15 79075000 79125000 190 | chr15 84775000 84825000 chr15 85875000 85925000 191 | chr15 83875000 83925000 chr15 84975000 85025000 192 | chr15 92925000 92975000 chr15 93825000 93875000 193 | chr15 91625000 91675000 chr15 93225000 93275000 194 | chr15 97125000 97175000 chr15 98625000 98675000 195 | chr15 100225000 100275000 chr15 101325000 101375000 196 | chr16 475000 525000 chr16 2275000 2325000 197 | chr16 9025000 9075000 chr16 10725000 10775000 198 | chr16 10525000 10575000 chr16 12525000 12575000 199 | chr16 25325000 25375000 chr16 27325000 27375000 200 | chr16 48625000 48675000 chr16 49725000 49775000 201 | chr16 49525000 49575000 chr16 50925000 50975000 202 | chr16 50875000 50925000 chr16 52975000 53025000 203 | chr16 52825000 52875000 chr16 53625000 53675000 204 | chr16 55875000 55925000 chr16 59575000 59625000 205 | chr16 68375000 68425000 chr16 69175000 69225000 206 | chr16 73825000 73875000 chr16 76225000 76275000 207 | chr16 71425000 71475000 chr16 72225000 72275000 208 | chr16 72075000 72125000 chr16 74475000 74525000 209 | chr16 77125000 77175000 chr16 78025000 78075000 210 | chr16 80525000 80575000 chr16 82525000 82575000 211 | chr16 81525000 81575000 chr16 84425000 84475000 212 | chr16 79375000 79425000 chr16 80775000 80825000 213 | chr17 4775000 4825000 chr17 7075000 7125000 214 | chr17 2575000 2625000 chr17 3675000 3725000 215 | chr17 6625000 6675000 chr17 8825000 8875000 216 | chr17 18075000 18125000 chr17 18975000 19025000 217 | chr17 19975000 20025000 chr17 20875000 20925000 218 | chr17 38475000 38525000 chr17 40075000 40125000 219 | chr17 39775000 39825000 chr17 41475000 41525000 220 | chr17 40975000 41025000 chr17 42275000 42325000 221 | chr17 51875000 51925000 chr17 53075000 53125000 222 | chr17 53725000 53775000 chr17 54725000 54775000 223 | chr17 58075000 58125000 chr17 60475000 60525000 224 | chr17 64875000 64925000 chr17 66475000 66525000 225 | chr17 68525000 68575000 chr17 70325000 70375000 226 | chr17 70775000 70825000 chr17 71575000 71625000 227 | chr17 70975000 71025000 chr17 72575000 72625000 228 | chr18 925000 975000 chr18 2625000 2675000 229 | chr18 19375000 19425000 chr18 20975000 21025000 230 | chr18 20525000 20575000 chr18 21425000 21475000 231 | chr18 22125000 22175000 chr18 23425000 23475000 232 | chr18 23375000 23425000 chr18 24175000 24225000 233 | chr18 43075000 43125000 chr18 44175000 44225000 234 | chr18 46075000 46125000 chr18 46875000 46925000 235 | chr18 48925000 48975000 chr18 51625000 51675000 236 | chr18 57825000 57875000 chr18 59725000 59775000 237 | chr18 73125000 73175000 chr18 74025000 74075000 238 | chr19 11875000 11925000 chr19 12675000 12725000 239 | chr19 30375000 30425000 chr19 33175000 33225000 240 | chr19 8625000 8675000 chr19 10225000 10275000 241 | chr19 19775000 19825000 chr19 21475000 21525000 242 | chr19 13175000 13225000 chr19 14075000 14125000 243 | chr19 14725000 14775000 chr19 16325000 16375000 244 | chr19 28475000 28525000 chr19 29575000 29625000 245 | chr19 36475000 36525000 chr19 38575000 38625000 246 | chr19 44275000 44325000 chr19 45075000 45125000 247 | chr19 39875000 39925000 chr19 40775000 40825000 248 | chr19 43025000 43075000 chr19 43925000 43975000 249 | chr19 52375000 52425000 chr19 54475000 54525000 250 | chr19 56525000 56575000 chr19 58825000 58875000 251 | chr2 6375000 6425000 chr2 7775000 7825000 252 | chr2 3725000 3775000 chr2 6925000 6975000 253 | chr2 7325000 7375000 chr2 8725000 8775000 254 | chr2 13175000 13225000 chr2 15075000 15125000 255 | chr2 15225000 15275000 chr2 16125000 16175000 256 | chr2 19675000 19725000 chr2 21275000 21325000 257 | chr2 20375000 20425000 chr2 24475000 24525000 258 | chr2 29225000 29275000 chr2 30425000 30475000 259 | chr2 37475000 37525000 chr2 38275000 38325000 260 | chr2 39675000 39725000 chr2 42375000 42425000 261 | chr2 42925000 42975000 chr2 43825000 43875000 262 | chr2 44325000 44375000 chr2 45225000 45275000 263 | chr2 51225000 51275000 chr2 52725000 52775000 264 | chr2 55025000 55075000 chr2 55825000 55875000 265 | chr2 59175000 59225000 chr2 60675000 60725000 266 | chr2 106625000 106675000 chr2 108925000 108975000 267 | chr2 64225000 64275000 chr2 66225000 66275000 268 | chr2 65575000 65625000 chr2 68575000 68625000 269 | chr2 69175000 69225000 chr2 71275000 71325000 270 | chr2 71125000 71175000 chr2 73825000 73875000 271 | chr2 105625000 105675000 chr2 106525000 106575000 272 | chr2 108525000 108575000 chr2 110025000 110075000 273 | chr2 120375000 120425000 chr2 121175000 121225000 274 | chr2 121875000 121925000 chr2 122875000 122925000 275 | chr2 129075000 129125000 chr2 130875000 130925000 276 | chr2 133225000 133275000 chr2 134425000 134475000 277 | chr2 138575000 138625000 chr2 139675000 139725000 278 | chr2 183175000 183225000 chr2 184575000 184625000 279 | chr2 137375000 137425000 chr2 138475000 138525000 280 | chr2 144475000 144525000 chr2 145875000 145925000 281 | chr2 149875000 149925000 chr2 152075000 152125000 282 | chr2 159725000 159775000 chr2 160825000 160875000 283 | chr2 179625000 179675000 chr2 180725000 180775000 284 | chr2 198075000 198125000 chr2 199275000 199325000 285 | chr2 204925000 204975000 chr2 206725000 206775000 286 | chr2 214025000 214075000 chr2 215925000 215975000 287 | chr2 215975000 216025000 chr2 216775000 216825000 288 | chr2 217225000 217275000 chr2 218825000 218875000 289 | chr2 220625000 220675000 chr2 223525000 223575000 290 | chr2 223875000 223925000 chr2 224675000 224725000 291 | chr2 226575000 226625000 chr2 227475000 227525000 292 | chr2 228325000 228375000 chr2 230825000 230875000 293 | chr2 234475000 234525000 chr2 236175000 236225000 294 | chr2 235975000 236025000 chr2 236875000 236925000 295 | chr2 237725000 237775000 chr2 240225000 240275000 296 | chr2 237125000 237175000 chr2 238325000 238375000 297 | chr2 239225000 239275000 chr2 241425000 241475000 298 | chr20 1675000 1725000 chr20 2475000 2525000 299 | chr20 4075000 4125000 chr20 5775000 5825000 300 | chr20 14075000 14125000 chr20 16375000 16425000 301 | chr20 8675000 8725000 chr20 9475000 9525000 302 | chr20 12875000 12925000 chr20 14175000 14225000 303 | chr20 23625000 23675000 chr20 25025000 25075000 304 | chr20 18825000 18875000 chr20 19825000 19875000 305 | chr20 22375000 22425000 chr20 23775000 23825000 306 | chr20 20625000 20675000 chr20 21625000 21675000 307 | chr20 37575000 37625000 chr20 39475000 39525000 308 | chr20 38975000 39025000 chr20 40775000 40825000 309 | chr20 40325000 40375000 chr20 42025000 42075000 310 | chr20 43925000 43975000 chr20 45025000 45075000 311 | chr20 44675000 44725000 chr20 45875000 45925000 312 | chr20 45975000 46025000 chr20 47775000 47825000 313 | chr20 50275000 50325000 chr20 52075000 52125000 314 | chr20 51825000 51875000 chr20 52825000 52875000 315 | chr20 52775000 52825000 chr20 55075000 55125000 316 | chr20 55525000 55575000 chr20 56525000 56575000 317 | chr20 58275000 58325000 chr20 59975000 60025000 318 | chr21 17675000 17725000 chr21 18775000 18825000 319 | chr21 31475000 31525000 chr21 32775000 32825000 320 | chr21 38225000 38275000 chr21 39025000 39075000 321 | chr21 40975000 41025000 chr21 43175000 43225000 322 | chr22 20175000 20225000 chr22 22075000 22125000 323 | chr22 25175000 25225000 chr22 26775000 26825000 324 | chr22 26525000 26575000 chr22 27525000 27575000 325 | chr22 26825000 26875000 chr22 28425000 28475000 326 | chr22 39925000 39975000 chr22 40825000 40875000 327 | chr22 46075000 46125000 chr22 47575000 47625000 328 | chr3 26225000 26275000 chr3 27325000 27375000 329 | chr3 9175000 9225000 chr3 10875000 10925000 330 | chr3 10175000 10225000 chr3 12675000 12725000 331 | chr3 17325000 17375000 chr3 18125000 18175000 332 | chr3 24025000 24075000 chr3 24825000 24875000 333 | chr3 34825000 34875000 chr3 35925000 35975000 334 | chr3 59875000 59925000 chr3 61175000 61225000 335 | chr3 57025000 57075000 chr3 58825000 58875000 336 | chr3 71575000 71625000 chr3 73175000 73225000 337 | chr3 75525000 75575000 chr3 76725000 76775000 338 | chr3 73675000 73725000 chr3 75375000 75425000 339 | chr3 100625000 100675000 chr3 101925000 101975000 340 | chr3 108875000 108925000 chr3 110075000 110125000 341 | chr3 109825000 109875000 chr3 110625000 110675000 342 | chr3 112025000 112075000 chr3 112925000 112975000 343 | chr3 120225000 120275000 chr3 121225000 121275000 344 | chr3 137625000 137675000 chr3 139525000 139575000 345 | chr3 130975000 131025000 chr3 132075000 132125000 346 | chr3 134375000 134425000 chr3 135375000 135425000 347 | chr3 136675000 136725000 chr3 137875000 137925000 348 | chr3 138725000 138775000 chr3 141225000 141275000 349 | chr3 167975000 168025000 chr3 169475000 169525000 350 | chr3 176375000 176425000 chr3 177675000 177725000 351 | chr3 178525000 178575000 chr3 179425000 179475000 352 | chr3 186075000 186125000 chr3 187075000 187125000 353 | chr3 184225000 184275000 chr3 185125000 185175000 354 | chr3 191075000 191125000 chr3 192375000 192425000 355 | chr4 4475000 4525000 chr4 6275000 6325000 356 | chr4 6025000 6075000 chr4 7625000 7675000 357 | chr4 9625000 9675000 chr4 10725000 10775000 358 | chr4 12525000 12575000 chr4 14225000 14275000 359 | chr4 13875000 13925000 chr4 14975000 15025000 360 | chr4 16225000 16275000 chr4 17125000 17175000 361 | chr4 22475000 22525000 chr4 24475000 24525000 362 | chr4 47925000 47975000 chr4 48925000 48975000 363 | chr4 53675000 53725000 chr4 54875000 54925000 364 | chr4 58325000 58375000 chr4 59125000 59175000 365 | chr4 69175000 69225000 chr4 70175000 70225000 366 | chr4 74675000 74725000 chr4 75775000 75825000 367 | chr4 76875000 76925000 chr4 78975000 79025000 368 | chr4 79025000 79075000 chr4 80225000 80275000 369 | chr4 106975000 107025000 chr4 108375000 108425000 370 | chr4 111525000 111575000 chr4 112925000 112975000 371 | chr4 117575000 117625000 chr4 118875000 118925000 372 | chr4 120875000 120925000 chr4 122075000 122125000 373 | chr4 141575000 141625000 chr4 144275000 144325000 374 | chr4 144275000 144325000 chr4 145575000 145625000 375 | chr4 148775000 148825000 chr4 150575000 150625000 376 | chr4 151175000 151225000 chr4 151975000 152025000 377 | chr4 152175000 152225000 chr4 153375000 153425000 378 | chr4 164425000 164475000 chr4 166125000 166175000 379 | chr4 159475000 159525000 chr4 160275000 160325000 380 | chr4 171275000 171325000 chr4 172975000 173025000 381 | chr4 173475000 173525000 chr4 174775000 174825000 382 | chr5 9325000 9375000 chr5 11325000 11375000 383 | chr5 8075000 8125000 chr5 9175000 9225000 384 | chr5 5975000 6025000 chr5 7275000 7325000 385 | chr5 12225000 12275000 chr5 13025000 13075000 386 | chr5 14175000 14225000 chr5 17075000 17125000 387 | chr5 15825000 15875000 chr5 17125000 17175000 388 | chr5 31325000 31375000 chr5 33125000 33175000 389 | chr5 34325000 34375000 chr5 35225000 35275000 390 | chr5 35125000 35175000 chr5 36125000 36175000 391 | chr5 38325000 38375000 chr5 39825000 39875000 392 | chr5 53025000 53075000 chr5 54225000 54275000 393 | chr5 62325000 62375000 chr5 64025000 64075000 394 | chr5 66525000 66575000 chr5 67425000 67475000 395 | chr5 73025000 73075000 chr5 74325000 74375000 396 | chr5 76325000 76375000 chr5 77325000 77375000 397 | chr5 78175000 78225000 chr5 79475000 79525000 398 | chr5 86775000 86825000 chr5 88075000 88125000 399 | chr5 88225000 88275000 chr5 89725000 89775000 400 | chr5 94325000 94375000 chr5 95925000 95975000 401 | chr5 96175000 96225000 chr5 98275000 98325000 402 | chr5 99975000 100025000 chr5 101375000 101425000 403 | chr5 115925000 115975000 chr5 117725000 117775000 404 | chr5 113125000 113175000 chr5 114525000 114575000 405 | chr5 125275000 125325000 chr5 126975000 127025000 406 | chr5 123425000 123475000 chr5 124625000 124675000 407 | chr5 124225000 124275000 chr5 125525000 125575000 408 | chr5 134675000 134725000 chr5 137675000 137725000 409 | chr5 144675000 144725000 chr5 146275000 146325000 410 | chr5 139825000 139875000 chr5 141325000 141375000 411 | chr5 156525000 156575000 chr5 157625000 157675000 412 | chr5 146075000 146125000 chr5 147675000 147725000 413 | chr5 150525000 150575000 chr5 154225000 154275000 414 | chr5 154275000 154325000 chr5 157075000 157125000 415 | chr5 157625000 157675000 chr5 158425000 158475000 416 | chr5 158825000 158875000 chr5 160425000 160475000 417 | chr5 169925000 169975000 chr5 170825000 170875000 418 | chr5 173775000 173825000 chr5 175075000 175125000 419 | chr5 175625000 175675000 chr5 177225000 177275000 420 | chr6 10125000 10175000 chr6 11325000 11375000 421 | chr6 7625000 7675000 chr6 10825000 10875000 422 | chr6 17125000 17175000 chr6 18625000 18675000 423 | chr6 11775000 11825000 chr6 13675000 13725000 424 | chr6 18375000 18425000 chr6 20075000 20125000 425 | chr6 19375000 19425000 chr6 21575000 21625000 426 | chr6 22175000 22225000 chr6 24175000 24225000 427 | chr6 46875000 46925000 chr6 50175000 50225000 428 | chr6 37525000 37575000 chr6 38825000 38875000 429 | chr6 39175000 39225000 chr6 41375000 41425000 430 | chr6 44675000 44725000 chr6 45575000 45625000 431 | chr6 45975000 46025000 chr6 46775000 46825000 432 | chr6 46625000 46675000 chr6 48125000 48175000 433 | chr6 49625000 49675000 chr6 51025000 51075000 434 | chr6 53775000 53825000 chr6 56475000 56525000 435 | chr6 71425000 71475000 chr6 73125000 73175000 436 | chr6 74375000 74425000 chr6 76275000 76325000 437 | chr6 84275000 84325000 chr6 85175000 85225000 438 | chr6 79425000 79475000 chr6 80225000 80275000 439 | chr6 80925000 80975000 chr6 82825000 82875000 440 | chr6 85925000 85975000 chr6 86825000 86875000 441 | chr6 86475000 86525000 chr6 87675000 87725000 442 | chr6 87775000 87825000 chr6 88775000 88825000 443 | chr6 146475000 146525000 chr6 148375000 148425000 444 | chr6 127825000 127875000 chr6 129325000 129375000 445 | chr6 97375000 97425000 chr6 99775000 99825000 446 | chr6 109775000 109825000 chr6 111075000 111125000 447 | chr6 123825000 123875000 chr6 125225000 125275000 448 | chr6 114525000 114575000 chr6 116225000 116275000 449 | chr6 118625000 118675000 chr6 120125000 120175000 450 | chr6 116425000 116475000 chr6 117425000 117475000 451 | chr6 147775000 147825000 chr6 149275000 149325000 452 | chr6 135125000 135175000 chr6 135925000 135975000 453 | chr6 138225000 138275000 chr6 139725000 139775000 454 | chr6 154525000 154575000 chr6 155625000 155675000 455 | chr6 155275000 155325000 chr6 157175000 157225000 456 | chr6 163525000 163575000 chr6 164625000 164675000 457 | chr6 161975000 162025000 chr6 163975000 164025000 458 | chr6 168525000 168575000 chr6 169825000 169875000 459 | chr7 1575000 1625000 chr7 2475000 2525000 460 | chr7 2625000 2675000 chr7 5025000 5075000 461 | chr7 9275000 9325000 chr7 10375000 10425000 462 | chr7 27825000 27875000 chr7 29625000 29675000 463 | chr7 23625000 23675000 chr7 24925000 24975000 464 | chr7 30625000 30675000 chr7 32925000 32975000 465 | chr7 32125000 32175000 chr7 33725000 33775000 466 | chr7 35425000 35475000 chr7 37025000 37075000 467 | chr7 36525000 36575000 chr7 38125000 38175000 468 | chr7 38375000 38425000 chr7 39675000 39725000 469 | chr7 47925000 47975000 chr7 49725000 49775000 470 | chr7 43575000 43625000 chr7 45475000 45525000 471 | chr7 78825000 78875000 chr7 80125000 80175000 472 | chr7 69875000 69925000 chr7 71675000 71725000 473 | chr7 71175000 71225000 chr7 72175000 72225000 474 | chr7 75875000 75925000 chr7 77375000 77425000 475 | chr7 83825000 83875000 chr7 84625000 84675000 476 | chr7 87875000 87925000 chr7 89775000 89825000 477 | chr7 102575000 102625000 chr7 104675000 104725000 478 | chr7 105125000 105175000 chr7 106425000 106475000 479 | chr7 110225000 110275000 chr7 111125000 111175000 480 | chr7 112825000 112875000 chr7 116025000 116075000 481 | chr7 117625000 117675000 chr7 118925000 118975000 482 | chr7 121375000 121425000 chr7 123175000 123225000 483 | chr7 122625000 122675000 chr7 123825000 123875000 484 | chr7 135925000 135975000 chr7 137325000 137375000 485 | chr7 132825000 132875000 chr7 133825000 133875000 486 | chr7 151575000 151625000 chr7 152775000 152825000 487 | chr7 152775000 152825000 chr7 154575000 154625000 488 | chr7 156725000 156775000 chr7 158825000 158875000 489 | chr8 8425000 8475000 chr8 9425000 9475000 490 | chr8 12875000 12925000 chr8 15375000 15425000 491 | chr8 56125000 56175000 chr8 57425000 57475000 492 | chr8 39975000 40025000 chr8 40875000 40925000 493 | chr8 54175000 54225000 chr8 55675000 55725000 494 | chr8 54825000 54875000 chr8 56925000 56975000 495 | chr8 59625000 59675000 chr8 61225000 61275000 496 | chr8 62825000 62875000 chr8 64025000 64075000 497 | chr8 64075000 64125000 chr8 65575000 65625000 498 | chr8 68725000 68775000 chr8 71125000 71175000 499 | chr8 70725000 70775000 chr8 71825000 71875000 500 | chr8 71175000 71225000 chr8 73275000 73325000 501 | chr8 78175000 78225000 chr8 79375000 79425000 502 | chr8 95275000 95325000 chr8 96875000 96925000 503 | chr8 102325000 102375000 chr8 103125000 103175000 504 | chr8 97525000 97575000 chr8 98325000 98375000 505 | chr8 102875000 102925000 chr8 104275000 104325000 506 | chr8 117175000 117225000 chr8 118375000 118425000 507 | chr8 123775000 123825000 chr8 124675000 124725000 508 | chr8 123975000 124025000 chr8 126075000 126125000 509 | chr8 134525000 134575000 chr8 135625000 135675000 510 | chr8 141125000 141175000 chr8 142725000 142775000 511 | chr8 142225000 142275000 chr8 144125000 144175000 512 | chr9 2725000 2775000 chr9 4125000 4175000 513 | chr9 4325000 4375000 chr9 5525000 5575000 514 | chr9 15875000 15925000 chr9 18075000 18125000 515 | chr9 18275000 18325000 chr9 20075000 20125000 516 | chr9 72725000 72775000 chr9 73525000 73575000 517 | chr9 73725000 73775000 chr9 74825000 74875000 518 | chr9 75825000 75875000 chr9 77625000 77675000 519 | chr9 77675000 77725000 chr9 78975000 79025000 520 | chr9 85725000 85775000 chr9 87225000 87275000 521 | chr9 86675000 86725000 chr9 88375000 88425000 522 | chr9 88775000 88825000 chr9 90175000 90225000 523 | chr9 104875000 104925000 chr9 106775000 106825000 524 | chr9 101775000 101825000 chr9 103075000 103125000 525 | chr9 116925000 116975000 chr9 119625000 119675000 526 | chr9 118575000 118625000 chr9 119575000 119625000 527 | chr9 123325000 123375000 chr9 124125000 124175000 528 | chr9 126025000 126075000 chr9 127125000 127175000 529 | chr9 134225000 134275000 chr9 136025000 136075000 530 | chr9 135375000 135425000 chr9 136675000 136725000 531 | chrX 13825000 13875000 chrX 15425000 15475000 532 | chrX 10875000 10925000 chrX 11875000 11925000 533 | chrX 11925000 11975000 chrX 12725000 12775000 534 | chrX 12775000 12825000 chrX 14075000 14125000 535 | chrX 15425000 15475000 chrX 17025000 17075000 536 | chrX 20475000 20525000 chrX 21875000 21925000 537 | chrX 22075000 22125000 chrX 23275000 23325000 538 | chrX 30125000 30175000 chrX 31525000 31575000 539 | chrX 43925000 43975000 chrX 45325000 45375000 540 | chrX 52825000 52875000 chrX 53725000 53775000 541 | chrX 64725000 64775000 chrX 65725000 65775000 542 | chrX 65875000 65925000 chrX 67275000 67325000 543 | chrX 68375000 68425000 chrX 69475000 69525000 544 | chrX 76225000 76275000 chrX 77825000 77875000 545 | chrX 79375000 79425000 chrX 80175000 80225000 546 | chrX 99525000 99575000 chrX 101225000 101275000 547 | chrX 102075000 102125000 chrX 102875000 102925000 548 | chrX 104325000 104375000 chrX 105425000 105475000 549 | chrX 107175000 107225000 chrX 109075000 109125000 550 | chrX 108475000 108525000 chrX 110375000 110425000 551 | chrX 111925000 111975000 chrX 114825000 114875000 552 | chrX 117825000 117875000 chrX 118925000 118975000 553 | chrX 131225000 131275000 chrX 133625000 133675000 554 | chrX 137525000 137575000 chrX 139025000 139075000 555 | chrX 150975000 151025000 chrX 151775000 151825000 556 | >>>>>>> fd3f9c132494aa3a0536aa90e5f7d71514f59a00 557 | -------------------------------------------------------------------------------- /Fountain/mESC/mES_WT_totalS_100kb_bs.bedpe: -------------------------------------------------------------------------------- 1 | <<<<<<< HEAD 2 | version https://git-lfs.github.com/spec/v1 3 | oid sha256:b32963476aefe28180edef3557945784e1b465e06835e38cdcf7afa8a8a8449d 4 | size 18470 5 | ======= 6 | chr1 x1 x2 chr2 y1 y2 7 | chr1 20550000 20650000 chr1 24350000 24450000 8 | chr1 31350000 31450000 chr1 33150000 33250000 9 | chr1 34450000 34550000 chr1 36250000 36350000 10 | chr1 39950000 40050000 chr1 43550000 43650000 11 | chr1 51150000 51250000 chr1 55550000 55650000 12 | chr1 54050000 54150000 chr1 58650000 58750000 13 | chr1 60850000 60950000 chr1 62850000 62950000 14 | chr1 73950000 74050000 chr1 75550000 75650000 15 | chr1 80050000 80150000 chr1 83050000 83150000 16 | chr1 82450000 82550000 chr1 84850000 84950000 17 | chr1 104950000 105050000 chr1 106950000 107050000 18 | chr1 115150000 115250000 chr1 117150000 117250000 19 | chr1 126050000 126150000 chr1 130050000 130150000 20 | chr1 128250000 128350000 chr1 131050000 131150000 21 | chr1 140350000 140450000 chr1 143550000 143650000 22 | chr1 146750000 146850000 chr1 150350000 150450000 23 | chr1 150850000 150950000 chr1 153850000 153950000 24 | chr1 154750000 154850000 chr1 157950000 158050000 25 | chr1 157050000 157150000 chr1 160250000 160350000 26 | chr1 167750000 167850000 chr1 170150000 170250000 27 | chr1 183250000 183350000 chr1 184850000 184950000 28 | chr1 183650000 183750000 chr1 188650000 188750000 29 | chr10 22550000 22650000 chr10 24150000 24250000 30 | chr10 14250000 14350000 chr10 17850000 17950000 31 | chr10 34550000 34650000 chr10 36750000 36850000 32 | chr10 30950000 31050000 chr10 34150000 34250000 33 | chr10 5550000 5650000 chr10 7750000 7850000 34 | chr10 47250000 47350000 chr10 48850000 48950000 35 | chr10 54250000 54350000 chr10 55850000 55950000 36 | chr10 110650000 110750000 chr10 112250000 112350000 37 | chr10 92250000 92350000 chr10 96850000 96950000 38 | chr10 96450000 96550000 chr10 98850000 98950000 39 | chr10 100250000 100350000 chr10 102850000 102950000 40 | chr10 125650000 125750000 chr10 130050000 130150000 41 | chr10 106850000 106950000 chr10 110050000 110150000 42 | chr10 123450000 123550000 chr10 125250000 125350000 43 | chr10 108250000 108350000 chr10 111250000 111350000 44 | chr11 11150000 11250000 chr11 13350000 13450000 45 | chr11 8550000 8650000 chr11 12150000 12250000 46 | chr11 19050000 19150000 chr11 24650000 24750000 47 | chr11 24250000 24350000 chr11 25850000 25950000 48 | chr11 40850000 40950000 chr11 43650000 43750000 49 | chr11 36650000 36750000 chr11 40250000 40350000 50 | chr11 46350000 46450000 chr11 48950000 49050000 51 | chr11 50050000 50150000 chr11 51850000 51950000 52 | chr11 49350000 49450000 chr11 55750000 55850000 53 | chr11 26250000 26350000 chr11 29650000 29750000 54 | chr11 55350000 55450000 chr11 57750000 57850000 55 | chr11 72750000 72850000 chr11 74950000 75050000 56 | chr11 68550000 68650000 chr11 70750000 70850000 57 | chr11 70650000 70750000 chr11 72650000 72750000 58 | chr11 80850000 80950000 chr11 82650000 82750000 59 | chr11 78250000 78350000 chr11 79850000 79950000 60 | chr11 90850000 90950000 chr11 93250000 93350000 61 | chr11 94450000 94550000 chr11 98850000 98950000 62 | chr11 98450000 98550000 chr11 101050000 101150000 63 | chr11 109650000 109750000 chr11 113450000 113550000 64 | chr11 117850000 117950000 chr11 120050000 120150000 65 | chr11 118850000 118950000 chr11 121450000 121550000 66 | chr12 12450000 12550000 chr12 17250000 17350000 67 | chr12 7550000 7650000 chr12 9750000 9850000 68 | chr12 5250000 5350000 chr12 8250000 8350000 69 | chr12 8950000 9050000 chr12 10950000 11050000 70 | chr12 28550000 28650000 chr12 31550000 31650000 71 | chr12 32950000 33050000 chr12 36150000 36250000 72 | chr12 49350000 49450000 chr12 50950000 51050000 73 | chr12 51450000 51550000 chr12 55650000 55750000 74 | chr12 53850000 53950000 chr12 56850000 56950000 75 | chr12 64050000 64150000 chr12 66650000 66750000 76 | chr12 65250000 65350000 chr12 69250000 69350000 77 | chr12 75150000 75250000 chr12 77350000 77450000 78 | chr12 80550000 80650000 chr12 84350000 84450000 79 | chr12 84050000 84150000 chr12 86850000 86950000 80 | chr12 78850000 78950000 chr12 80850000 80950000 81 | chr12 72450000 72550000 chr12 76850000 76950000 82 | chr12 96150000 96250000 chr12 97750000 97850000 83 | chr12 105750000 105850000 chr12 108350000 108450000 84 | chr12 89950000 90050000 chr12 93150000 93250000 85 | chr12 109450000 109550000 chr12 112650000 112750000 86 | chr12 108750000 108850000 chr12 110750000 110850000 87 | chr13 8950000 9050000 chr13 12350000 12450000 88 | chr13 25450000 25550000 chr13 28650000 28750000 89 | chr13 37650000 37750000 chr13 41650000 41750000 90 | chr13 38850000 38950000 chr13 43050000 43150000 91 | chr13 46650000 46750000 chr13 49050000 49150000 92 | chr13 53450000 53550000 chr13 57650000 57750000 93 | chr13 56350000 56450000 chr13 57950000 58050000 94 | chr13 67750000 67850000 chr13 69550000 69650000 95 | chr13 81550000 81650000 chr13 84150000 84250000 96 | chr13 115150000 115250000 chr13 116750000 116850000 97 | chr13 105050000 105150000 chr13 106650000 106750000 98 | chr14 8450000 8550000 chr14 11650000 11750000 99 | chr14 14550000 14650000 chr14 16150000 16250000 100 | chr14 12550000 12650000 chr14 14150000 14250000 101 | chr14 20050000 20150000 chr14 21850000 21950000 102 | chr14 21550000 21650000 chr14 24150000 24250000 103 | chr14 25350000 25450000 chr14 27350000 27450000 104 | chr14 27250000 27350000 chr14 30650000 30750000 105 | chr14 29550000 29650000 chr14 33350000 33450000 106 | chr14 34650000 34750000 chr14 40850000 40950000 107 | chr14 52450000 52550000 chr14 54050000 54150000 108 | chr14 57550000 57650000 chr14 59750000 59850000 109 | chr14 67650000 67750000 chr14 70450000 70550000 110 | chr14 70550000 70650000 chr14 72950000 73050000 111 | chr14 101450000 101550000 chr14 103650000 103750000 112 | chr14 118550000 118650000 chr14 120950000 121050000 113 | chr14 99650000 99750000 chr14 101650000 101750000 114 | chr15 17150000 17250000 chr15 18950000 19050000 115 | chr15 19550000 19650000 chr15 21350000 21450000 116 | chr15 24650000 24750000 chr15 26250000 26350000 117 | chr15 27750000 27850000 chr15 30550000 30650000 118 | chr15 25750000 25850000 chr15 27950000 28050000 119 | chr15 34350000 34450000 chr15 36350000 36450000 120 | chr15 39650000 39750000 chr15 41250000 41350000 121 | chr15 76450000 76550000 chr15 79650000 79750000 122 | chr15 55450000 55550000 chr15 58250000 58350000 123 | chr15 66750000 66850000 chr15 68350000 68450000 124 | chr15 68750000 68850000 chr15 71950000 72050000 125 | chr15 86150000 86250000 chr15 88750000 88850000 126 | chr15 88350000 88450000 chr15 89950000 90050000 127 | chr15 79750000 79850000 chr15 81750000 81850000 128 | chr16 10450000 10550000 chr16 14050000 14150000 129 | chr16 8450000 8550000 chr16 11250000 11350000 130 | chr16 10050000 10150000 chr16 12050000 12150000 131 | chr16 20350000 20450000 chr16 22150000 22250000 132 | chr16 11650000 11750000 chr16 15650000 15750000 133 | chr16 14150000 14250000 chr16 15750000 15850000 134 | chr16 35850000 35950000 chr16 38250000 38350000 135 | chr16 33750000 33850000 chr16 35350000 35450000 136 | chr16 24850000 24950000 chr16 29850000 29950000 137 | chr16 30350000 30450000 chr16 32550000 32650000 138 | chr16 45850000 45950000 chr16 48450000 48550000 139 | chr16 59850000 59950000 chr16 62650000 62750000 140 | chr16 63950000 64050000 chr16 66550000 66650000 141 | chr16 79250000 79350000 chr16 81050000 81150000 142 | chr16 72550000 72650000 chr16 77150000 77250000 143 | chr16 84850000 84950000 chr16 87650000 87750000 144 | chr16 92450000 92550000 chr16 95650000 95750000 145 | chr16 87850000 87950000 chr16 89850000 89950000 146 | chr16 91850000 91950000 chr16 94050000 94150000 147 | chr17 3550000 3650000 chr17 5150000 5250000 148 | chr17 10350000 10450000 chr17 12150000 12250000 149 | chr17 17650000 17750000 chr17 21450000 21550000 150 | chr17 43350000 43450000 chr17 45350000 45450000 151 | chr17 29650000 29750000 chr17 31650000 31750000 152 | chr17 38150000 38250000 chr17 40350000 40450000 153 | chr17 43850000 43950000 chr17 49650000 49750000 154 | chr17 54050000 54150000 chr17 55650000 55750000 155 | chr17 55350000 55450000 chr17 57550000 57650000 156 | chr17 64950000 65050000 chr17 67550000 67650000 157 | chr17 75350000 75450000 chr17 78550000 78650000 158 | chr17 77350000 77450000 chr17 81750000 81850000 159 | chr17 80350000 80450000 chr17 83750000 83850000 160 | chr17 70950000 71050000 chr17 74750000 74850000 161 | chr17 88950000 89050000 chr17 90550000 90650000 162 | chr17 90450000 90550000 chr17 93850000 93950000 163 | chr18 23350000 23450000 chr18 25550000 25650000 164 | chr18 7750000 7850000 chr18 9350000 9450000 165 | chr18 20450000 20550000 chr18 24650000 24750000 166 | chr18 32150000 32250000 chr18 33950000 34050000 167 | chr18 31850000 31950000 chr18 38450000 38550000 168 | chr18 50250000 50350000 chr18 53050000 53150000 169 | chr18 46950000 47050000 chr18 49950000 50050000 170 | chr18 53950000 54050000 chr18 56350000 56450000 171 | chr18 55650000 55750000 chr18 58650000 58750000 172 | chr18 59650000 59750000 chr18 62850000 62950000 173 | chr18 61850000 61950000 chr18 64050000 64150000 174 | chr18 65250000 65350000 chr18 67850000 67950000 175 | chr18 71150000 71250000 chr18 73350000 73450000 176 | chr18 79750000 79850000 chr18 83150000 83250000 177 | chr18 80650000 80750000 chr18 84650000 84750000 178 | chr18 82350000 82450000 chr18 85150000 85250000 179 | chr18 77850000 77950000 chr18 80250000 80350000 180 | chr19 12150000 12250000 chr19 14550000 14650000 181 | chr19 25450000 25550000 chr19 27850000 27950000 182 | chr19 18750000 18850000 chr19 21350000 21450000 183 | chr19 30150000 30250000 chr19 32150000 32250000 184 | chr19 31850000 31950000 chr19 35450000 35550000 185 | chr19 36350000 36450000 chr19 38950000 39050000 186 | chr2 20650000 20750000 chr2 25250000 25350000 187 | chr2 48450000 48550000 chr2 53450000 53550000 188 | chr2 6550000 6650000 chr2 9750000 9850000 189 | chr2 4250000 4350000 chr2 6650000 6750000 190 | chr2 40950000 41050000 chr2 43950000 44050000 191 | chr2 35050000 35150000 chr2 38450000 38550000 192 | chr2 37050000 37150000 chr2 39650000 39750000 193 | chr2 43750000 43850000 chr2 45750000 45850000 194 | chr2 58850000 58950000 chr2 61050000 61150000 195 | chr2 65850000 65950000 chr2 68850000 68950000 196 | chr2 64850000 64950000 chr2 66850000 66950000 197 | chr2 29450000 29550000 chr2 33450000 33550000 198 | chr2 80950000 81050000 chr2 83350000 83450000 199 | chr2 73750000 73850000 chr2 75550000 75650000 200 | chr2 87450000 87550000 chr2 90650000 90750000 201 | chr2 110250000 110350000 chr2 112050000 112150000 202 | chr2 118350000 118450000 chr2 122150000 122250000 203 | chr2 127350000 127450000 chr2 130750000 130850000 204 | chr2 133050000 133150000 chr2 135250000 135350000 205 | chr2 137650000 137750000 chr2 139450000 139550000 206 | chr2 122450000 122550000 chr2 125450000 125550000 207 | chr2 146750000 146850000 chr2 150350000 150450000 208 | chr2 145450000 145550000 chr2 147650000 147750000 209 | chr2 158950000 159050000 chr2 160550000 160650000 210 | chr2 158250000 158350000 chr2 163450000 163550000 211 | chr2 160850000 160950000 chr2 163250000 163350000 212 | chr2 170450000 170550000 chr2 172450000 172550000 213 | chr3 21050000 21150000 chr3 22850000 22950000 214 | chr3 10550000 10650000 chr3 14550000 14650000 215 | chr3 8350000 8450000 chr3 10750000 10850000 216 | chr3 14050000 14150000 chr3 16650000 16750000 217 | chr3 30750000 30850000 chr3 32750000 32850000 218 | chr3 28050000 28150000 chr3 30850000 30950000 219 | chr3 38050000 38150000 chr3 40650000 40750000 220 | chr3 65650000 65750000 chr3 68650000 68750000 221 | chr3 53250000 53350000 chr3 54850000 54950000 222 | chr3 55050000 55150000 chr3 57650000 57750000 223 | chr3 114750000 114850000 chr3 117950000 118050000 224 | chr3 73650000 73750000 chr3 78050000 78150000 225 | chr3 75650000 75750000 chr3 79050000 79150000 226 | chr3 81050000 81150000 chr3 84250000 84350000 227 | chr3 97050000 97150000 chr3 101850000 101950000 228 | chr3 104550000 104650000 chr3 108350000 108450000 229 | chr3 107450000 107550000 chr3 109050000 109150000 230 | chr3 94950000 95050000 chr3 96950000 97050000 231 | chr3 120750000 120850000 chr3 123550000 123650000 232 | chr3 135450000 135550000 chr3 138250000 138350000 233 | chr3 130950000 131050000 chr3 133350000 133450000 234 | chr3 131250000 131350000 chr3 135450000 135550000 235 | chr3 127250000 127350000 chr3 130050000 130150000 236 | chr3 132450000 132550000 chr3 136250000 136350000 237 | chr3 142550000 142650000 chr3 144950000 145050000 238 | chr3 146850000 146950000 chr3 148850000 148950000 239 | chr3 138850000 138950000 chr3 142450000 142550000 240 | chr3 149750000 149850000 chr3 151350000 151450000 241 | chr4 8450000 8550000 chr4 11250000 11350000 242 | chr4 12050000 12150000 chr4 14650000 14750000 243 | chr4 35250000 35350000 chr4 40450000 40550000 244 | chr4 29350000 29450000 chr4 31350000 31450000 245 | chr4 32650000 32750000 chr4 35050000 35150000 246 | chr4 41450000 41550000 chr4 43250000 43350000 247 | chr4 48950000 49050000 chr4 52950000 53050000 248 | chr4 55350000 55450000 chr4 56950000 57050000 249 | chr4 56850000 56950000 chr4 59450000 59550000 250 | chr4 59950000 60050000 chr4 61950000 62050000 251 | chr4 24550000 24650000 chr4 26750000 26850000 252 | chr4 70250000 70350000 chr4 74250000 74350000 253 | chr4 119750000 119850000 chr4 124350000 124450000 254 | chr4 85150000 85250000 chr4 86750000 86850000 255 | chr4 91850000 91950000 chr4 93850000 93950000 256 | chr4 95150000 95250000 chr4 98350000 98450000 257 | chr4 98250000 98350000 chr4 100050000 100150000 258 | chr4 99050000 99150000 chr4 101650000 101750000 259 | chr4 100150000 100250000 chr4 102750000 102850000 260 | chr4 99550000 99650000 chr4 106950000 107050000 261 | chr4 111650000 111750000 chr4 115250000 115350000 262 | chr4 126450000 126550000 chr4 129650000 129750000 263 | chr4 127550000 127650000 chr4 132150000 132250000 264 | chr4 129650000 129750000 chr4 132850000 132950000 265 | chr4 151250000 151350000 chr4 153450000 153550000 266 | chr5 7550000 7650000 chr5 9750000 9850000 267 | chr5 9850000 9950000 chr5 12850000 12950000 268 | chr5 21450000 21550000 chr5 23650000 23750000 269 | chr5 32450000 32550000 chr5 34650000 34750000 270 | chr5 25550000 25650000 chr5 27750000 27850000 271 | chr5 39050000 39150000 chr5 41250000 41350000 272 | chr5 45850000 45950000 chr5 48250000 48350000 273 | chr5 6050000 6150000 chr5 7650000 7750000 274 | chr5 63950000 64050000 chr5 66150000 66250000 275 | chr5 73250000 73350000 chr5 76250000 76350000 276 | chr5 83950000 84050000 chr5 85550000 85650000 277 | chr5 86150000 86250000 chr5 88750000 88850000 278 | chr5 88750000 88850000 chr5 90350000 90450000 279 | chr5 100450000 100550000 chr5 103850000 103950000 280 | chr5 107250000 107350000 chr5 111250000 111350000 281 | chr5 140250000 140350000 chr5 142850000 142950000 282 | chr5 135750000 135850000 chr5 137550000 137650000 283 | chr5 142650000 142750000 chr5 145050000 145150000 284 | chr5 143850000 143950000 chr5 147850000 147950000 285 | chr5 146650000 146750000 chr5 150850000 150950000 286 | chr6 14250000 14350000 chr6 17050000 17150000 287 | chr6 73550000 73650000 chr6 76750000 76850000 288 | chr6 30650000 30750000 chr6 34650000 34750000 289 | chr6 34550000 34650000 chr6 38150000 38250000 290 | chr6 37250000 37350000 chr6 40250000 40350000 291 | chr6 51150000 51250000 chr6 52950000 53050000 292 | chr6 49250000 49350000 chr6 51650000 51750000 293 | chr6 87750000 87850000 chr6 91950000 92050000 294 | chr6 94450000 94550000 chr6 97650000 97750000 295 | chr6 99250000 99350000 chr6 101050000 101150000 296 | chr6 97050000 97150000 chr6 100450000 100550000 297 | chr6 112350000 112450000 chr6 116750000 116850000 298 | chr6 116250000 116350000 chr6 117850000 117950000 299 | chr6 122750000 122850000 chr6 124750000 124850000 300 | chr6 126850000 126950000 chr6 129050000 129150000 301 | chr6 129450000 129550000 chr6 131050000 131150000 302 | chr6 112950000 113050000 chr6 118350000 118450000 303 | chr6 143050000 143150000 chr6 148850000 148950000 304 | chr6 143050000 143150000 chr6 145050000 145150000 305 | chr6 140350000 140450000 chr6 143150000 143250000 306 | chr6 133550000 133650000 chr6 135750000 135850000 307 | chr6 137550000 137650000 chr6 140150000 140250000 308 | chr7 16550000 16650000 chr7 19350000 19450000 309 | chr7 35950000 36050000 chr7 37550000 37650000 310 | chr7 31150000 31250000 chr7 34150000 34250000 311 | chr7 33850000 33950000 chr7 36050000 36150000 312 | chr7 43850000 43950000 chr7 46450000 46550000 313 | chr7 46750000 46850000 chr7 49350000 49450000 314 | chr7 48050000 48150000 chr7 51050000 51150000 315 | chr7 72150000 72250000 chr7 74350000 74450000 316 | chr7 78850000 78950000 chr7 82050000 82150000 317 | chr7 81850000 81950000 chr7 83850000 83950000 318 | chr7 108750000 108850000 chr7 111550000 111650000 319 | chr7 90350000 90450000 chr7 92550000 92650000 320 | chr7 110450000 110550000 chr7 112850000 112950000 321 | chr7 93150000 93250000 chr7 95550000 95650000 322 | chr7 107650000 107750000 chr7 109250000 109350000 323 | chr7 114650000 114750000 chr7 120050000 120150000 324 | chr7 115750000 115850000 chr7 120950000 121050000 325 | chr7 128750000 128850000 chr7 130550000 130650000 326 | chr7 123550000 123650000 chr7 125550000 125650000 327 | chr7 125650000 125750000 chr7 128650000 128750000 328 | chr7 110850000 110950000 chr7 115850000 115950000 329 | chr7 130350000 130450000 chr7 133550000 133650000 330 | chr8 58050000 58150000 chr8 60450000 60550000 331 | chr8 22350000 22450000 chr8 25950000 26050000 332 | chr8 25350000 25450000 chr8 27350000 27450000 333 | chr8 43450000 43550000 chr8 45050000 45150000 334 | chr8 54350000 54450000 chr8 56550000 56650000 335 | chr8 87550000 87650000 chr8 92150000 92250000 336 | chr8 75350000 75450000 chr8 77350000 77450000 337 | chr8 81250000 81350000 chr8 82850000 82950000 338 | chr8 83250000 83350000 chr8 85650000 85750000 339 | chr8 59450000 59550000 chr8 63250000 63350000 340 | chr8 91350000 91450000 chr8 94550000 94650000 341 | chr8 112250000 112350000 chr8 114050000 114150000 342 | chr8 107650000 107750000 chr8 109250000 109350000 343 | chr8 93850000 93950000 chr8 95850000 95950000 344 | chr8 60450000 60550000 chr8 65650000 65750000 345 | chr8 117250000 117350000 chr8 119850000 119950000 346 | chr9 3850000 3950000 chr9 7850000 7950000 347 | chr9 15650000 15750000 chr9 17650000 17750000 348 | chr9 20150000 20250000 chr9 22950000 23050000 349 | chr9 22850000 22950000 chr9 25050000 25150000 350 | chr9 27350000 27450000 chr9 30950000 31050000 351 | chr9 34750000 34850000 chr9 37350000 37450000 352 | chr9 32550000 32650000 chr9 34750000 34850000 353 | chr9 45750000 45850000 chr9 49150000 49250000 354 | chr9 48750000 48850000 chr9 50750000 50850000 355 | chr9 49350000 49450000 chr9 54750000 54850000 356 | chr9 55150000 55250000 chr9 57150000 57250000 357 | chr9 30450000 30550000 chr9 32250000 32350000 358 | chr9 25150000 25250000 chr9 27150000 27250000 359 | chr9 92650000 92750000 chr9 94650000 94750000 360 | chr9 65250000 65350000 chr9 67250000 67350000 361 | chr9 67450000 67550000 chr9 70050000 70150000 362 | chr9 69450000 69550000 chr9 71250000 71350000 363 | chr9 73350000 73450000 chr9 74950000 75050000 364 | chr9 75150000 75250000 chr9 78350000 78450000 365 | chr9 70250000 70350000 chr9 72850000 72950000 366 | chr9 80350000 80450000 chr9 82750000 82850000 367 | chr9 84250000 84350000 chr9 85850000 85950000 368 | chr9 85650000 85750000 chr9 87250000 87350000 369 | chr9 86950000 87050000 chr9 88550000 88650000 370 | chr9 95050000 95150000 chr9 97450000 97550000 371 | chr9 97150000 97250000 chr9 98950000 99050000 372 | chr9 97450000 97550000 chr9 102650000 102750000 373 | chr9 108150000 108250000 chr9 110350000 110450000 374 | chr9 110450000 110550000 chr9 114650000 114750000 375 | chrX 11750000 11850000 chrX 13950000 14050000 376 | chrX 13950000 14050000 chrX 16950000 17050000 377 | chrX 21550000 21650000 chrX 23550000 23650000 378 | chrX 38350000 38450000 chrX 41950000 42050000 379 | chrX 53750000 53850000 chrX 56150000 56250000 380 | chrX 68950000 69050000 chrX 70550000 70650000 381 | chrX 109150000 109250000 chrX 111350000 111450000 382 | chrX 129050000 129150000 chrX 131450000 131550000 383 | chrX 131150000 131250000 chrX 133750000 133850000 384 | chrX 134250000 134350000 chrX 135850000 135950000 385 | chrX 138650000 138750000 chrX 141250000 141350000 386 | chrX 137350000 137450000 chrX 138950000 139050000 387 | chrX 86450000 86550000 chrX 88250000 88350000 388 | chrX 150850000 150950000 chrX 152850000 152950000 389 | chrX 155150000 155250000 chrX 157550000 157650000 390 | chrX 162450000 162550000 chrX 164450000 164550000 391 | chrX 164050000 164150000 chrX 166650000 166750000 392 | chrX 167450000 167550000 chrX 169250000 169350000 393 | >>>>>>> fd3f9c132494aa3a0536aa90e5f7d71514f59a00 394 | -------------------------------------------------------------------------------- /Fountain/mESC/mES_WT_totalS_200kb_bs.bedpe: -------------------------------------------------------------------------------- 1 | <<<<<<< HEAD 2 | version https://git-lfs.github.com/spec/v1 3 | oid sha256:a57a0a027512c35d9706c6815d3cbe9086b5a3981374537d2194515ae44e7417 4 | size 8649 5 | ======= 6 | chr1 x1 x2 chr2 y1 y2 7 | chr1 6700000 6900000 chr1 9900000 10100000 8 | chr1 9500000 9700000 chr1 13100000 13300000 9 | chr1 96700000 96900000 chr1 106700000 106900000 10 | chr1 20700000 20900000 chr1 23900000 24100000 11 | chr1 33900000 34100000 chr1 39100000 39300000 12 | chr1 59900000 60100000 chr1 63900000 64100000 13 | chr1 94100000 94300000 chr1 97300000 97500000 14 | chr1 156100000 156300000 chr1 161300000 161500000 15 | chr1 117300000 117500000 chr1 122500000 122700000 16 | chr1 131300000 131500000 chr1 136900000 137100000 17 | chr1 151300000 151500000 chr1 156900000 157100000 18 | chr1 104100000 104300000 chr1 108100000 108300000 19 | chr1 156700000 156900000 chr1 164700000 164900000 20 | chr1 151100000 151300000 chr1 161900000 162100000 21 | chr1 164700000 164900000 chr1 172700000 172900000 22 | chr1 177100000 177300000 chr1 183100000 183300000 23 | chr1 188500000 188700000 chr1 194100000 194300000 24 | chr10 20300000 20500000 chr10 25100000 25300000 25 | chr10 13500000 13700000 chr10 18700000 18900000 26 | chr10 10900000 11100000 chr10 14900000 15100000 27 | chr10 7900000 8100000 chr10 13100000 13300000 28 | chr10 70900000 71100000 chr10 75300000 75500000 29 | chr10 58500000 58700000 chr10 63700000 63900000 30 | chr10 53300000 53500000 chr10 57300000 57500000 31 | chr10 63500000 63700000 chr10 67100000 67300000 32 | chr10 46100000 46300000 chr10 50900000 51100000 33 | chr10 38900000 39100000 chr10 44900000 45100000 34 | chr10 89500000 89700000 chr10 93900000 94100000 35 | chr10 84900000 85100000 chr10 88900000 89100000 36 | chr10 122500000 122700000 chr10 126500000 126700000 37 | chr10 115100000 115300000 chr10 123500000 123700000 38 | chr10 112100000 112300000 chr10 115300000 115500000 39 | chr11 12100000 12300000 chr11 17300000 17500000 40 | chr11 18300000 18500000 chr11 25500000 25700000 41 | chr11 49300000 49500000 chr11 55300000 55500000 42 | chr11 54500000 54700000 chr11 58100000 58300000 43 | chr11 115700000 115900000 chr11 120500000 120700000 44 | chr11 74700000 74900000 chr11 79500000 79700000 45 | chr11 80100000 80300000 chr11 83700000 83900000 46 | chr11 81700000 81900000 chr11 90100000 90300000 47 | chr11 54500000 54700000 chr11 67700000 67900000 48 | chr11 88100000 88300000 chr11 95300000 95500000 49 | chr11 95100000 95300000 chr11 103900000 104100000 50 | chr11 60700000 60900000 chr11 69900000 70100000 51 | chr12 16500000 16700000 chr12 25700000 25900000 52 | chr12 4700000 4900000 chr12 8300000 8500000 53 | chr12 51500000 51700000 chr12 55500000 55700000 54 | chr12 113100000 113300000 chr12 117100000 117300000 55 | chr12 72700000 72900000 chr12 76300000 76500000 56 | chr12 69300000 69500000 chr12 72900000 73100000 57 | chr12 80100000 80300000 chr12 84100000 84300000 58 | chr12 99300000 99500000 chr12 102900000 103100000 59 | chr12 105900000 106100000 chr12 109100000 109300000 60 | chr13 25100000 25300000 chr13 29100000 29300000 61 | chr13 34500000 34700000 chr13 38100000 38300000 62 | chr13 85100000 85300000 chr13 90300000 90500000 63 | chr13 58500000 58700000 chr13 63700000 63900000 64 | chr13 89300000 89500000 chr13 92500000 92700000 65 | chr13 114100000 114300000 chr13 118900000 119100000 66 | chr13 100100000 100300000 chr13 103700000 103900000 67 | chr14 25100000 25300000 chr14 33100000 33300000 68 | chr14 19700000 19900000 chr14 32100000 32300000 69 | chr14 19900000 20100000 chr14 27100000 27300000 70 | chr14 33900000 34100000 chr14 37100000 37300000 71 | chr14 57100000 57300000 chr14 60700000 60900000 72 | chr14 117700000 117900000 chr14 122900000 123100000 73 | chr15 67100000 67300000 chr15 73100000 73300000 74 | chr15 99300000 99500000 chr15 102500000 102700000 75 | chr16 13500000 13700000 chr16 18300000 18500000 76 | chr16 38100000 38300000 chr16 43300000 43500000 77 | chr16 16900000 17100000 chr16 21700000 21900000 78 | chr16 50700000 50900000 chr16 56300000 56500000 79 | chr16 44900000 45100000 chr16 49300000 49500000 80 | chr16 23100000 23300000 chr16 30700000 30900000 81 | chr16 90900000 91100000 chr16 94500000 94700000 82 | chr16 77500000 77700000 chr16 85100000 85300000 83 | chr17 4100000 4300000 chr17 8900000 9100000 84 | chr17 8300000 8500000 chr17 11900000 12100000 85 | chr17 43500000 43700000 chr17 50300000 50500000 86 | chr17 66100000 66300000 chr17 71300000 71500000 87 | chr17 74300000 74500000 chr17 79900000 80100000 88 | chr17 80100000 80300000 chr17 84100000 84300000 89 | chr17 83500000 83700000 chr17 88300000 88500000 90 | chr17 52100000 52300000 chr17 58100000 58300000 91 | chr18 19300000 19500000 chr18 26500000 26700000 92 | chr18 24500000 24700000 chr18 31700000 31900000 93 | chr18 57100000 57300000 chr18 61100000 61300000 94 | chr18 74300000 74500000 chr18 77900000 78100000 95 | chr18 79700000 79900000 chr18 86100000 86300000 96 | chr19 23700000 23900000 chr19 29700000 29900000 97 | chr19 12300000 12500000 chr19 16300000 16500000 98 | chr19 40700000 40900000 chr19 47100000 47300000 99 | chr2 14300000 14500000 chr2 17500000 17700000 100 | chr2 45300000 45500000 chr2 48900000 49100000 101 | chr2 48500000 48700000 chr2 53700000 53900000 102 | chr2 80100000 80300000 chr2 84500000 84700000 103 | chr2 123500000 123700000 chr2 134700000 134900000 104 | chr2 90500000 90700000 chr2 94500000 94700000 105 | chr2 90900000 91100000 chr2 104900000 105100000 106 | chr2 135900000 136100000 chr2 140300000 140500000 107 | chr2 118100000 118300000 chr2 122100000 122300000 108 | chr2 121900000 122100000 chr2 126300000 126500000 109 | chr2 147300000 147500000 chr2 150500000 150700000 110 | chr2 113500000 113700000 chr2 118300000 118500000 111 | chr2 158300000 158500000 chr2 163900000 164100000 112 | chr2 163500000 163700000 chr2 169500000 169700000 113 | chr2 152500000 152700000 chr2 157700000 157900000 114 | chr2 173300000 173500000 chr2 180100000 180300000 115 | chr3 80100000 80300000 chr3 84100000 84300000 116 | chr3 13500000 13700000 chr3 20300000 20500000 117 | chr3 37500000 37700000 chr3 40700000 40900000 118 | chr3 55300000 55500000 chr3 61300000 61500000 119 | chr3 54900000 55100000 chr3 58100000 58300000 120 | chr3 141900000 142100000 chr3 146300000 146500000 121 | chr3 88300000 88500000 chr3 96700000 96900000 122 | chr3 93700000 93900000 chr3 98100000 98300000 123 | chr3 100900000 101100000 chr3 104500000 104700000 124 | chr3 104700000 104900000 chr3 107900000 108100000 125 | chr3 115500000 115700000 chr3 123100000 123300000 126 | chr3 144900000 145100000 chr3 154900000 155100000 127 | chr4 119900000 120100000 chr4 123500000 123700000 128 | chr4 88500000 88700000 chr4 94500000 94700000 129 | chr4 104900000 105100000 chr4 110900000 111100000 130 | chr4 107900000 108100000 chr4 117900000 118100000 131 | chr4 115300000 115500000 chr4 120900000 121100000 132 | chr4 123300000 123500000 chr4 126500000 126700000 133 | chr4 126500000 126700000 chr4 129700000 129900000 134 | chr4 150700000 150900000 chr4 154700000 154900000 135 | chr5 64100000 64300000 chr5 67700000 67900000 136 | chr5 45900000 46100000 chr5 49100000 49300000 137 | chr5 49300000 49500000 chr5 52500000 52700000 138 | chr5 3900000 4100000 chr5 9100000 9300000 139 | chr5 67900000 68100000 chr5 72700000 72900000 140 | chr5 143100000 143300000 chr5 149900000 150100000 141 | chr5 124700000 124900000 chr5 129100000 129300000 142 | chr5 88300000 88500000 chr5 92700000 92900000 143 | chr5 113900000 114100000 chr5 123100000 123300000 144 | chr5 72300000 72500000 chr5 77900000 78100000 145 | chr5 130500000 130700000 chr5 134500000 134700000 146 | chr5 140500000 140700000 chr5 143700000 143900000 147 | chr6 33900000 34100000 chr6 39100000 39300000 148 | chr6 12300000 12500000 chr6 18300000 18500000 149 | chr6 36300000 36500000 chr6 41500000 41700000 150 | chr6 17100000 17300000 chr6 23500000 23700000 151 | chr6 61900000 62100000 chr6 70700000 70900000 152 | chr6 58900000 59100000 chr6 67700000 67900000 153 | chr6 101300000 101500000 chr6 107700000 107900000 154 | chr6 128500000 128700000 chr6 134100000 134300000 155 | chr6 82900000 83100000 chr6 88100000 88300000 156 | chr7 31100000 31300000 chr7 34300000 34500000 157 | chr7 19900000 20100000 chr7 23900000 24100000 158 | chr7 61300000 61500000 chr7 71300000 71500000 159 | chr7 67900000 68100000 chr7 72700000 72900000 160 | chr7 84100000 84300000 chr7 89300000 89500000 161 | chr7 110300000 110500000 chr7 113500000 113700000 162 | chr7 97100000 97300000 chr7 101900000 102100000 163 | chr7 133700000 133900000 chr7 139700000 139900000 164 | chr8 10700000 10900000 chr8 15500000 15700000 165 | chr8 4500000 4700000 chr8 10900000 11100000 166 | chr8 36500000 36700000 chr8 40100000 40300000 167 | chr8 57100000 57300000 chr8 61900000 62100000 168 | chr8 61300000 61500000 chr8 64900000 65100000 169 | chr8 69300000 69500000 chr8 72500000 72700000 170 | chr8 116900000 117100000 chr8 127700000 127900000 171 | chr8 104500000 104700000 chr8 112900000 113100000 172 | chr9 6700000 6900000 chr9 11100000 11300000 173 | chr9 8300000 8500000 chr9 15100000 15300000 174 | chr9 4100000 4300000 chr9 8100000 8300000 175 | chr9 49300000 49500000 chr9 54500000 54700000 176 | chr9 114500000 114700000 chr9 119700000 119900000 177 | chr9 65500000 65700000 chr9 72300000 72500000 178 | chr9 119900000 120100000 chr9 123100000 123300000 179 | chr9 99300000 99500000 chr9 103700000 103900000 180 | chrX 11100000 11300000 chrX 14300000 14500000 181 | chrX 6100000 6300000 chrX 9300000 9500000 182 | chrX 5900000 6100000 chrX 14700000 14900000 183 | chrX 47500000 47700000 chrX 53500000 53700000 184 | chrX 37700000 37900000 chrX 42100000 42300000 185 | chrX 94900000 95100000 chrX 99700000 99900000 186 | chrX 130500000 130700000 chrX 134100000 134300000 187 | >>>>>>> fd3f9c132494aa3a0536aa90e5f7d71514f59a00 188 | -------------------------------------------------------------------------------- /Fountain/mESC/mES_WT_totalS_50kb_bs.bedpe: -------------------------------------------------------------------------------- 1 | <<<<<<< HEAD 2 | version https://git-lfs.github.com/spec/v1 3 | oid sha256:c865aa0e4a5de73c3d78ea86d34ad1be8e15eb88f71d80b886c12e5c47b77258 4 | size 26674 5 | ======= 6 | chr1 x1 x2 chr2 y1 y2 7 | chr1 11575000 11625000 chr1 12775000 12825000 8 | chr1 14625000 14675000 chr1 15825000 15875000 9 | chr1 12525000 12575000 chr1 13825000 13875000 10 | chr1 19075000 19125000 chr1 20475000 20525000 11 | chr1 30275000 30325000 chr1 31575000 31625000 12 | chr1 34675000 34725000 chr1 35775000 35825000 13 | chr1 40975000 41025000 chr1 41875000 41925000 14 | chr1 45875000 45925000 chr1 46975000 47025000 15 | chr1 55075000 55125000 chr1 57375000 57425000 16 | chr1 61075000 61125000 chr1 62775000 62825000 17 | chr1 72375000 72425000 chr1 74275000 74325000 18 | chr1 75875000 75925000 chr1 77175000 77225000 19 | chr1 79625000 79675000 chr1 80725000 80775000 20 | chr1 82325000 82375000 chr1 83325000 83375000 21 | chr1 84975000 85025000 chr1 85775000 85825000 22 | chr1 92975000 93025000 chr1 93775000 93825000 23 | chr1 153325000 153375000 chr1 155725000 155775000 24 | chr1 103875000 103925000 chr1 104775000 104825000 25 | chr1 110275000 110325000 chr1 111375000 111425000 26 | chr1 120425000 120475000 chr1 121325000 121375000 27 | chr1 125675000 125725000 chr1 126975000 127025000 28 | chr1 128325000 128375000 chr1 131025000 131075000 29 | chr1 137425000 137475000 chr1 138825000 138875000 30 | chr1 145925000 145975000 chr1 146925000 146975000 31 | chr1 151675000 151725000 chr1 152775000 152825000 32 | chr1 164225000 164275000 chr1 165425000 165475000 33 | chr1 152275000 152325000 chr1 153975000 154025000 34 | chr1 166125000 166175000 chr1 167225000 167275000 35 | chr1 167825000 167875000 chr1 169925000 169975000 36 | chr1 171225000 171275000 chr1 172225000 172275000 37 | chr1 178425000 178475000 chr1 179425000 179475000 38 | chr1 174425000 174475000 chr1 175825000 175875000 39 | chr1 176875000 176925000 chr1 177675000 177725000 40 | chr1 179775000 179825000 chr1 180575000 180625000 41 | chr1 180125000 180175000 chr1 181325000 181375000 42 | chr1 193325000 193375000 chr1 195125000 195175000 43 | chr1 181475000 181525000 chr1 182775000 182825000 44 | chr1 183525000 183575000 chr1 184625000 184675000 45 | chr1 184775000 184825000 chr1 185675000 185725000 46 | chr1 166575000 166625000 chr1 168175000 168225000 47 | chr1 189875000 189925000 chr1 190875000 190925000 48 | chr10 7325000 7375000 chr10 8125000 8175000 49 | chr10 5975000 6025000 chr10 7175000 7225000 50 | chr10 3575000 3625000 chr10 4775000 4825000 51 | chr10 11475000 11525000 chr10 12275000 12325000 52 | chr10 19625000 19675000 chr10 20525000 20575000 53 | chr10 17575000 17625000 chr10 18375000 18425000 54 | chr10 40525000 40575000 chr10 41325000 41375000 55 | chr10 37225000 37275000 chr10 38825000 38875000 56 | chr10 36375000 36425000 chr10 37675000 37725000 57 | chr10 52225000 52275000 chr10 53525000 53575000 58 | chr10 56425000 56475000 chr10 57425000 57475000 59 | chr10 60175000 60225000 chr10 61175000 61225000 60 | chr10 66975000 67025000 chr10 68275000 68325000 61 | chr10 68375000 68425000 chr10 69175000 69225000 62 | chr10 72875000 72925000 chr10 74575000 74625000 63 | chr10 75625000 75675000 chr10 76525000 76575000 64 | chr10 64125000 64175000 chr10 65325000 65375000 65 | chr10 78325000 78375000 chr10 79725000 79775000 66 | chr10 83575000 83625000 chr10 84675000 84725000 67 | chr10 85825000 85875000 chr10 86725000 86775000 68 | chr10 90525000 90575000 chr10 91625000 91675000 69 | chr10 91225000 91275000 chr10 93125000 93175000 70 | chr10 107575000 107625000 chr10 108975000 109025000 71 | chr10 110425000 110475000 chr10 112025000 112075000 72 | chr10 118375000 118425000 chr10 119875000 119925000 73 | chr10 115475000 115525000 chr10 116375000 116425000 74 | chr10 129025000 129075000 chr10 130325000 130375000 75 | chr10 121975000 122025000 chr10 122875000 122925000 76 | chr10 123425000 123475000 chr10 125425000 125475000 77 | chr10 126975000 127025000 chr10 128775000 128825000 78 | chr11 8275000 8325000 chr11 9175000 9225000 79 | chr11 6875000 6925000 chr11 8575000 8625000 80 | chr11 16225000 16275000 chr11 17325000 17375000 81 | chr11 24025000 24075000 chr11 25925000 25975000 82 | chr11 33025000 33075000 chr11 33825000 33875000 83 | chr11 35425000 35475000 chr11 36325000 36375000 84 | chr11 45725000 45775000 chr11 46725000 46775000 85 | chr11 40625000 40675000 chr11 42125000 42175000 86 | chr11 42325000 42375000 chr11 43125000 43175000 87 | chr11 30875000 30925000 chr11 32175000 32225000 88 | chr11 50325000 50375000 chr11 51625000 51675000 89 | chr11 51375000 51425000 chr11 52575000 52625000 90 | chr11 52425000 52475000 chr11 53225000 53275000 91 | chr11 56175000 56225000 chr11 57175000 57225000 92 | chr11 58225000 58275000 chr11 59125000 59175000 93 | chr11 61825000 61875000 chr11 62625000 62675000 94 | chr11 44775000 44825000 chr11 45575000 45625000 95 | chr11 91225000 91275000 chr11 93225000 93275000 96 | chr11 68675000 68725000 chr11 70175000 70225000 97 | chr11 70925000 70975000 chr11 72225000 72275000 98 | chr11 71975000 72025000 chr11 73375000 73425000 99 | chr11 73075000 73125000 chr11 74575000 74625000 100 | chr11 76425000 76475000 chr11 77725000 77775000 101 | chr11 80775000 80825000 chr11 81575000 81625000 102 | chr11 80625000 80675000 chr11 82725000 82775000 103 | chr11 85375000 85425000 chr11 86175000 86225000 104 | chr11 88025000 88075000 chr11 88925000 88975000 105 | chr11 108975000 109025000 chr11 109875000 109925000 106 | chr11 97775000 97825000 chr11 98875000 98925000 107 | chr11 98875000 98925000 chr11 100575000 100625000 108 | chr11 102125000 102175000 chr11 103025000 103075000 109 | chr11 104475000 104525000 chr11 105975000 106025000 110 | chr11 113775000 113825000 chr11 114575000 114625000 111 | chr11 107875000 107925000 chr11 109175000 109225000 112 | chr11 118125000 118175000 chr11 119225000 119275000 113 | chr12 7675000 7725000 chr12 9575000 9625000 114 | chr12 8975000 9025000 chr12 10975000 11025000 115 | chr12 11425000 11475000 chr12 12325000 12375000 116 | chr12 12425000 12475000 chr12 13325000 13375000 117 | chr12 28275000 28325000 chr12 29375000 29425000 118 | chr12 28875000 28925000 chr12 31275000 31325000 119 | chr12 30825000 30875000 chr12 32225000 32275000 120 | chr12 42175000 42225000 chr12 42975000 43025000 121 | chr12 49425000 49475000 chr12 50925000 50975000 122 | chr12 52625000 52675000 chr12 54425000 54475000 123 | chr12 63425000 63475000 chr12 64625000 64675000 124 | chr12 70325000 70375000 chr12 71625000 71675000 125 | chr12 102725000 102775000 chr12 104725000 104775000 126 | chr12 74325000 74375000 chr12 75225000 75275000 127 | chr12 79225000 79275000 chr12 80225000 80275000 128 | chr12 83575000 83625000 chr12 84375000 84425000 129 | chr12 90925000 90975000 chr12 92225000 92275000 130 | chr12 102225000 102275000 chr12 103125000 103175000 131 | chr12 104225000 104275000 chr12 106325000 106375000 132 | chr12 110175000 110225000 chr12 112175000 112225000 133 | chr12 111675000 111725000 chr12 112875000 112925000 134 | chr12 105925000 105975000 chr12 108425000 108475000 135 | chr13 6725000 6775000 chr13 8725000 8775000 136 | chr13 12625000 12675000 chr13 13425000 13475000 137 | chr13 15575000 15625000 chr13 17575000 17625000 138 | chr13 21925000 21975000 chr13 23325000 23375000 139 | chr13 31525000 31575000 chr13 32925000 32975000 140 | chr13 34925000 34975000 chr13 35825000 35875000 141 | chr13 47125000 47175000 chr13 48525000 48575000 142 | chr13 49175000 49225000 chr13 51675000 51725000 143 | chr13 54575000 54625000 chr13 55475000 55525000 144 | chr13 58025000 58075000 chr13 60025000 60075000 145 | chr13 110075000 110125000 chr13 111475000 111525000 146 | chr13 64375000 64425000 chr13 65175000 65225000 147 | chr13 71025000 71075000 chr13 72025000 72075000 148 | chr13 83675000 83725000 chr13 84575000 84625000 149 | chr13 82125000 82175000 chr13 83525000 83575000 150 | chr13 105225000 105275000 chr13 106625000 106675000 151 | chr13 106675000 106725000 chr13 108375000 108425000 152 | chr13 108825000 108875000 chr13 110525000 110575000 153 | chr13 115025000 115075000 chr13 116725000 116775000 154 | chr14 11175000 11225000 chr14 12475000 12525000 155 | chr14 14875000 14925000 chr14 15975000 16025000 156 | chr14 21775000 21825000 chr14 24175000 24225000 157 | chr14 23875000 23925000 chr14 24675000 24725000 158 | chr14 21075000 21125000 chr14 21875000 21925000 159 | chr14 54375000 54425000 chr14 55975000 56025000 160 | chr14 33775000 33825000 chr14 35175000 35225000 161 | chr14 37975000 38025000 chr14 40075000 40125000 162 | chr14 45575000 45625000 chr14 47075000 47125000 163 | chr14 49925000 49975000 chr14 50825000 50875000 164 | chr14 46675000 46725000 chr14 48075000 48125000 165 | chr14 50975000 51025000 chr14 51975000 52025000 166 | chr14 58025000 58075000 chr14 59225000 59275000 167 | chr14 59575000 59625000 chr14 60775000 60825000 168 | chr14 61675000 61725000 chr14 62475000 62525000 169 | chr14 65775000 65825000 chr14 67075000 67125000 170 | chr14 71175000 71225000 chr14 72375000 72425000 171 | chr14 73325000 73375000 chr14 75025000 75075000 172 | chr14 77175000 77225000 chr14 77975000 78025000 173 | chr14 85875000 85925000 chr14 87975000 88025000 174 | chr14 98575000 98625000 chr14 100175000 100225000 175 | chr14 101775000 101825000 chr14 102975000 103025000 176 | chr14 110975000 111025000 chr14 111775000 111825000 177 | chr14 103875000 103925000 chr14 104875000 104925000 178 | chr14 102875000 102925000 chr14 103675000 103725000 179 | chr14 123175000 123225000 chr14 124475000 124525000 180 | chr14 119075000 119125000 chr14 120075000 120125000 181 | chr15 6275000 6325000 chr15 7675000 7725000 182 | chr15 10175000 10225000 chr15 11075000 11125000 183 | chr15 7725000 7775000 chr15 8725000 8775000 184 | chr15 26275000 26325000 chr15 27375000 27425000 185 | chr15 19575000 19625000 chr15 21475000 21525000 186 | chr15 25275000 25325000 chr15 26275000 26325000 187 | chr15 32775000 32825000 chr15 34075000 34125000 188 | chr15 41025000 41075000 chr15 42025000 42075000 189 | chr15 42025000 42075000 chr15 43025000 43075000 190 | chr15 43925000 43975000 chr15 44825000 44875000 191 | chr15 40125000 40175000 chr15 41125000 41175000 192 | chr15 82125000 82175000 chr15 83225000 83275000 193 | chr15 51475000 51525000 chr15 52375000 52425000 194 | chr15 54925000 54975000 chr15 55725000 55775000 195 | chr15 55575000 55625000 chr15 57975000 58025000 196 | chr15 64375000 64425000 chr15 65875000 65925000 197 | chr15 72775000 72825000 chr15 73975000 74025000 198 | chr15 74825000 74875000 chr15 75625000 75675000 199 | chr15 82425000 82475000 chr15 84025000 84075000 200 | chr15 83475000 83525000 chr15 84675000 84725000 201 | chr15 88425000 88475000 chr15 89625000 89675000 202 | chr15 93175000 93225000 chr15 94775000 94825000 203 | chr15 92425000 92475000 chr15 93225000 93275000 204 | chr15 102225000 102275000 chr15 103425000 103475000 205 | chr16 3725000 3775000 chr16 5125000 5175000 206 | chr16 8775000 8825000 chr16 10475000 10525000 207 | chr16 11375000 11425000 chr16 13275000 13325000 208 | chr16 13375000 13425000 chr16 14275000 14325000 209 | chr16 14325000 14375000 chr16 15825000 15875000 210 | chr16 15825000 15875000 chr16 17125000 17175000 211 | chr16 19075000 19125000 chr16 19975000 20025000 212 | chr16 21525000 21575000 chr16 22625000 22675000 213 | chr16 26125000 26175000 chr16 27125000 27175000 214 | chr16 42875000 42925000 chr16 43675000 43725000 215 | chr16 46375000 46425000 chr16 48075000 48125000 216 | chr16 48125000 48175000 chr16 48925000 48975000 217 | chr16 51025000 51075000 chr16 52325000 52375000 218 | chr16 57625000 57675000 chr16 58425000 58475000 219 | chr16 58525000 58575000 chr16 59525000 59575000 220 | chr16 62775000 62825000 chr16 64875000 64925000 221 | chr16 77975000 78025000 chr16 78775000 78825000 222 | chr16 96225000 96275000 chr16 97725000 97775000 223 | chr16 84425000 84475000 chr16 85325000 85375000 224 | chr16 87675000 87725000 chr16 89975000 90025000 225 | chr16 95125000 95175000 chr16 96725000 96775000 226 | chr16 94575000 94625000 chr16 95975000 96025000 227 | chr16 93325000 93375000 chr16 95125000 95175000 228 | chr17 3425000 3475000 chr17 5125000 5175000 229 | chr17 46775000 46825000 chr17 47575000 47625000 230 | chr17 6975000 7025000 chr17 7975000 8025000 231 | chr17 9925000 9975000 chr17 10725000 10775000 232 | chr17 24625000 24675000 chr17 26125000 26175000 233 | chr17 15825000 15875000 chr17 16725000 16775000 234 | chr17 17525000 17575000 chr17 21425000 21475000 235 | chr17 14075000 14125000 chr17 14975000 15025000 236 | chr17 33925000 33975000 chr17 34925000 34975000 237 | chr17 36475000 36525000 chr17 37675000 37725000 238 | chr17 45575000 45625000 chr17 46675000 46725000 239 | chr17 79675000 79725000 chr17 80975000 81025000 240 | chr17 53725000 53775000 chr17 55825000 55875000 241 | chr17 55725000 55775000 chr17 57325000 57375000 242 | chr17 57825000 57875000 chr17 58725000 58775000 243 | chr17 65425000 65475000 chr17 66725000 66775000 244 | chr17 67275000 67325000 chr17 68475000 68525000 245 | chr17 67825000 67875000 chr17 69325000 69375000 246 | chr17 71725000 71775000 chr17 74225000 74275000 247 | chr17 73075000 73125000 chr17 74075000 74125000 248 | chr17 78875000 78925000 chr17 80175000 80225000 249 | chr17 81175000 81225000 chr17 82075000 82125000 250 | chr18 3375000 3425000 chr18 4475000 4525000 251 | chr18 6625000 6675000 chr18 7625000 7675000 252 | chr18 8125000 8175000 chr18 9125000 9175000 253 | chr18 10625000 10675000 chr18 11925000 11975000 254 | chr18 12875000 12925000 chr18 14775000 14825000 255 | chr18 20125000 20175000 chr18 21525000 21575000 256 | chr18 14225000 14275000 chr18 15325000 15375000 257 | chr18 31975000 32025000 chr18 34375000 34425000 258 | chr18 36825000 36875000 chr18 37625000 37675000 259 | chr18 39125000 39175000 chr18 40125000 40175000 260 | chr18 45025000 45075000 chr18 45925000 45975000 261 | chr18 46175000 46225000 chr18 46975000 47025000 262 | chr18 49425000 49475000 chr18 50425000 50475000 263 | chr18 56225000 56275000 chr18 57125000 57175000 264 | chr18 53975000 54025000 chr18 56175000 56225000 265 | chr18 65875000 65925000 chr18 67275000 67325000 266 | chr18 77625000 77675000 chr18 80325000 80375000 267 | chr18 82725000 82775000 chr18 84725000 84775000 268 | chr18 89025000 89075000 chr18 90225000 90275000 269 | chr19 9125000 9175000 chr19 9925000 9975000 270 | chr19 7375000 7425000 chr19 8775000 8825000 271 | chr19 3875000 3925000 chr19 4975000 5025000 272 | chr19 9625000 9675000 chr19 11125000 11175000 273 | chr19 14275000 14325000 chr19 15175000 15225000 274 | chr19 12925000 12975000 chr19 14025000 14075000 275 | chr19 17525000 17575000 chr19 18325000 18375000 276 | chr19 23075000 23125000 chr19 24275000 24325000 277 | chr19 29725000 29775000 chr19 32625000 32675000 278 | chr19 33075000 33125000 chr19 34775000 34825000 279 | chr19 35025000 35075000 chr19 36125000 36175000 280 | chr19 42125000 42175000 chr19 43925000 43975000 281 | chr19 38975000 39025000 chr19 40275000 40325000 282 | chr19 44125000 44175000 chr19 45025000 45075000 283 | chr19 52725000 52775000 chr19 54225000 54275000 284 | chr19 59475000 59525000 chr19 60275000 60325000 285 | chr19 53575000 53625000 chr19 55575000 55625000 286 | chr2 3625000 3675000 chr2 4625000 4675000 287 | chr2 4675000 4725000 chr2 6175000 6225000 288 | chr2 10175000 10225000 chr2 11675000 11725000 289 | chr2 21125000 21175000 chr2 22825000 22875000 290 | chr2 23225000 23275000 chr2 24725000 24775000 291 | chr2 26425000 26475000 chr2 27525000 27575000 292 | chr2 36175000 36225000 chr2 37375000 37425000 293 | chr2 37725000 37775000 chr2 38725000 38775000 294 | chr2 27675000 27725000 chr2 28475000 28525000 295 | chr2 80175000 80225000 chr2 81075000 81125000 296 | chr2 57225000 57275000 chr2 58625000 58675000 297 | chr2 59225000 59275000 chr2 60725000 60775000 298 | chr2 61625000 61675000 chr2 62425000 62475000 299 | chr2 64625000 64675000 chr2 66625000 66675000 300 | chr2 70975000 71025000 chr2 71975000 72025000 301 | chr2 71725000 71775000 chr2 73025000 73075000 302 | chr2 77825000 77875000 chr2 79325000 79375000 303 | chr2 83625000 83675000 chr2 84825000 84875000 304 | chr2 88225000 88275000 chr2 89825000 89875000 305 | chr2 90775000 90825000 chr2 91675000 91725000 306 | chr2 93425000 93475000 chr2 94625000 94675000 307 | chr2 105275000 105325000 chr2 106275000 106325000 308 | chr2 117225000 117275000 chr2 118225000 118275000 309 | chr2 112825000 112875000 chr2 113825000 113875000 310 | chr2 127725000 127775000 chr2 128725000 128775000 311 | chr2 128725000 128775000 chr2 129525000 129575000 312 | chr2 129225000 129275000 chr2 130525000 130575000 313 | chr2 132975000 133025000 chr2 135475000 135525000 314 | chr2 139725000 139775000 chr2 140525000 140575000 315 | chr2 142925000 142975000 chr2 144125000 144175000 316 | chr2 143525000 143575000 chr2 144925000 144975000 317 | chr2 144775000 144825000 chr2 145675000 145725000 318 | chr2 153475000 153525000 chr2 154575000 154625000 319 | chr2 164975000 165025000 chr2 165775000 165825000 320 | chr2 158625000 158675000 chr2 160725000 160775000 321 | chr2 160325000 160375000 chr2 161325000 161375000 322 | chr2 160675000 160725000 chr2 163275000 163325000 323 | chr2 170125000 170175000 chr2 172725000 172775000 324 | chr2 165975000 166025000 chr2 167075000 167125000 325 | chr2 168975000 169025000 chr2 170075000 170125000 326 | chr2 178075000 178125000 chr2 179975000 180025000 327 | chr2 180025000 180075000 chr2 181525000 181575000 328 | chr3 7525000 7575000 chr3 8425000 8475000 329 | chr3 18125000 18175000 chr3 19125000 19175000 330 | chr3 20575000 20625000 chr3 21375000 21425000 331 | chr3 30425000 30475000 chr3 31225000 31275000 332 | chr3 23475000 23525000 chr3 25175000 25225000 333 | chr3 30725000 30775000 chr3 32825000 32875000 334 | chr3 32125000 32175000 chr3 33125000 33175000 335 | chr3 32375000 32425000 chr3 34275000 34325000 336 | chr3 35225000 35275000 chr3 36325000 36375000 337 | chr3 36325000 36375000 chr3 37425000 37475000 338 | chr3 73675000 73725000 chr3 75075000 75125000 339 | chr3 54125000 54175000 chr3 55525000 55575000 340 | chr3 66175000 66225000 chr3 67275000 67325000 341 | chr3 61225000 61275000 chr3 62125000 62175000 342 | chr3 78925000 78975000 chr3 79825000 79875000 343 | chr3 79975000 80025000 chr3 80775000 80825000 344 | chr3 80425000 80475000 chr3 81725000 81775000 345 | chr3 81875000 81925000 chr3 82975000 83025000 346 | chr3 89275000 89325000 chr3 90075000 90125000 347 | chr3 106025000 106075000 chr3 107325000 107375000 348 | chr3 75225000 75275000 chr3 76125000 76175000 349 | chr3 113875000 113925000 chr3 115475000 115525000 350 | chr3 119825000 119875000 chr3 120825000 120875000 351 | chr3 127075000 127125000 chr3 130175000 130225000 352 | chr3 129225000 129275000 chr3 130125000 130175000 353 | chr3 131675000 131725000 chr3 132475000 132525000 354 | chr3 132375000 132425000 chr3 133975000 134025000 355 | chr3 133625000 133675000 chr3 135225000 135275000 356 | chr3 143125000 143175000 chr3 144225000 144275000 357 | chr3 154675000 154725000 chr3 156275000 156325000 358 | chr3 156325000 156375000 chr3 157325000 157375000 359 | chr3 158225000 158275000 chr3 159625000 159675000 360 | chr4 6475000 6525000 chr4 8275000 8325000 361 | chr4 28225000 28275000 chr4 29525000 29575000 362 | chr4 33475000 33525000 chr4 34475000 34525000 363 | chr4 55525000 55575000 chr4 56825000 56875000 364 | chr4 53875000 53925000 chr4 55075000 55125000 365 | chr4 59925000 59975000 chr4 62225000 62275000 366 | chr4 83825000 83875000 chr4 84925000 84975000 367 | chr4 91925000 91975000 chr4 92925000 92975000 368 | chr4 99375000 99425000 chr4 101575000 101625000 369 | chr4 100925000 100975000 chr4 102025000 102075000 370 | chr4 103375000 103425000 chr4 104775000 104825000 371 | chr4 105275000 105325000 chr4 106275000 106325000 372 | chr4 110025000 110075000 chr4 111725000 111775000 373 | chr4 101875000 101925000 chr4 102975000 103025000 374 | chr4 118225000 118275000 chr4 119225000 119275000 375 | chr4 119275000 119325000 chr4 120675000 120725000 376 | chr4 120125000 120175000 chr4 121225000 121275000 377 | chr4 123675000 123725000 chr4 124875000 124925000 378 | chr4 114925000 114975000 chr4 115925000 115975000 379 | chr4 125975000 126025000 chr4 127275000 127325000 380 | chr4 127125000 127175000 chr4 129125000 129175000 381 | chr4 130525000 130575000 chr4 132325000 132375000 382 | chr4 124825000 124875000 chr4 126325000 126375000 383 | chr4 137175000 137225000 chr4 138075000 138125000 384 | chr4 142225000 142275000 chr4 143125000 143175000 385 | chr4 150975000 151025000 chr4 151775000 151825000 386 | chr4 151475000 151525000 chr4 152875000 152925000 387 | chr4 152575000 152625000 chr4 153775000 153825000 388 | chr4 154175000 154225000 chr4 154975000 155025000 389 | chr5 7675000 7725000 chr5 9675000 9725000 390 | chr5 5775000 5825000 chr5 8075000 8125000 391 | chr5 10625000 10675000 chr5 12225000 12275000 392 | chr5 21875000 21925000 chr5 23375000 23425000 393 | chr5 27625000 27675000 chr5 28525000 28575000 394 | chr5 28475000 28525000 chr5 29275000 29325000 395 | chr5 29925000 29975000 chr5 30825000 30875000 396 | chr5 31325000 31375000 chr5 32825000 32875000 397 | chr5 34675000 34725000 chr5 35475000 35525000 398 | chr5 34525000 34575000 chr5 36825000 36875000 399 | chr5 35525000 35575000 chr5 37125000 37175000 400 | chr5 42025000 42075000 chr5 43425000 43475000 401 | chr5 43125000 43175000 chr5 44825000 44875000 402 | chr5 44375000 44425000 chr5 45275000 45325000 403 | chr5 50225000 50275000 chr5 52225000 52275000 404 | chr5 49425000 49475000 chr5 50625000 50675000 405 | chr5 4975000 5025000 chr5 5975000 6025000 406 | chr5 67925000 67975000 chr5 69525000 69575000 407 | chr5 102175000 102225000 chr5 103275000 103325000 408 | chr5 111175000 111225000 chr5 112375000 112425000 409 | chr5 108275000 108325000 chr5 110075000 110125000 410 | chr5 114425000 114475000 chr5 115725000 115775000 411 | chr5 117475000 117525000 chr5 119275000 119325000 412 | chr5 118675000 118725000 chr5 120375000 120425000 413 | chr5 124425000 124475000 chr5 125425000 125475000 414 | chr5 125375000 125425000 chr5 127575000 127625000 415 | chr5 127575000 127625000 chr5 128575000 128625000 416 | chr5 132775000 132825000 chr5 133775000 133825000 417 | chr5 145075000 145125000 chr5 146575000 146625000 418 | chr5 140625000 140675000 chr5 142525000 142575000 419 | chr6 15825000 15875000 chr6 16925000 16975000 420 | chr6 31775000 31825000 chr6 32775000 32825000 421 | chr6 24125000 24175000 chr6 25025000 25075000 422 | chr6 24825000 24875000 chr6 25725000 25775000 423 | chr6 35275000 35325000 chr6 37275000 37325000 424 | chr6 52975000 53025000 chr6 53875000 53925000 425 | chr6 47725000 47775000 chr6 49225000 49275000 426 | chr6 55275000 55325000 chr6 56575000 56625000 427 | chr6 64925000 64975000 chr6 67125000 67175000 428 | chr6 66375000 66425000 chr6 67975000 68025000 429 | chr6 67975000 68025000 chr6 69975000 70025000 430 | chr6 38425000 38475000 chr6 39425000 39475000 431 | chr6 83775000 83825000 chr6 85275000 85325000 432 | chr6 84675000 84725000 chr6 87275000 87325000 433 | chr6 86325000 86375000 chr6 88425000 88475000 434 | chr6 89575000 89625000 chr6 90475000 90525000 435 | chr6 96775000 96825000 chr6 98175000 98225000 436 | chr6 99375000 99425000 chr6 101175000 101225000 437 | chr6 107825000 107875000 chr6 108925000 108975000 438 | chr6 112525000 112575000 chr6 114025000 114075000 439 | chr6 113775000 113825000 chr6 114775000 114825000 440 | chr6 119375000 119425000 chr6 120275000 120325000 441 | chr6 121175000 121225000 chr6 122475000 122525000 442 | chr6 122925000 122975000 chr6 124425000 124475000 443 | chr6 124075000 124125000 chr6 125975000 126025000 444 | chr6 125575000 125625000 chr6 126875000 126925000 445 | chr6 116625000 116675000 chr6 117725000 117775000 446 | chr6 131725000 131775000 chr6 132825000 132875000 447 | chr6 135475000 135525000 chr6 136275000 136325000 448 | chr6 140075000 140125000 chr6 141075000 141125000 449 | chr6 140575000 140625000 chr6 142975000 143025000 450 | chr6 142475000 142525000 chr6 143475000 143525000 451 | chr6 142625000 142675000 chr6 145525000 145575000 452 | chr6 144725000 144775000 chr6 145625000 145675000 453 | chr6 145175000 145225000 chr6 146675000 146725000 454 | chr6 147125000 147175000 chr6 148125000 148175000 455 | chr7 3425000 3475000 chr7 4725000 4775000 456 | chr7 5225000 5275000 chr7 6025000 6075000 457 | chr7 29175000 29225000 chr7 29975000 30025000 458 | chr7 25375000 25425000 chr7 27575000 27625000 459 | chr7 27525000 27575000 chr7 28325000 28375000 460 | chr7 43425000 43475000 chr7 44425000 44475000 461 | chr7 39725000 39775000 chr7 41025000 41075000 462 | chr7 47125000 47175000 chr7 48925000 48975000 463 | chr7 50225000 50275000 chr7 51825000 51875000 464 | chr7 55575000 55625000 chr7 56375000 56425000 465 | chr7 33525000 33575000 chr7 36225000 36275000 466 | chr7 63575000 63625000 chr7 64475000 64525000 467 | chr7 68725000 68775000 chr7 70325000 70375000 468 | chr7 74775000 74825000 chr7 76575000 76625000 469 | chr7 73675000 73725000 chr7 75675000 75725000 470 | chr7 102575000 102625000 chr7 104075000 104125000 471 | chr7 92275000 92325000 chr7 93075000 93125000 472 | chr7 100425000 100475000 chr7 102225000 102275000 473 | chr7 106925000 106975000 chr7 107825000 107875000 474 | chr7 107925000 107975000 chr7 108825000 108875000 475 | chr7 111075000 111125000 chr7 112175000 112225000 476 | chr7 115725000 115775000 chr7 116825000 116875000 477 | chr7 116725000 116775000 chr7 117925000 117975000 478 | chr7 117725000 117775000 chr7 119325000 119375000 479 | chr7 113925000 113975000 chr7 116525000 116575000 480 | chr7 118975000 119025000 chr7 119775000 119825000 481 | chr7 120825000 120875000 chr7 122125000 122175000 482 | chr7 121475000 121525000 chr7 123775000 123825000 483 | chr7 123675000 123725000 chr7 125475000 125525000 484 | chr7 72425000 72475000 chr7 73525000 73575000 485 | chr7 137575000 137625000 chr7 138775000 138825000 486 | chr7 126125000 126175000 chr7 128125000 128175000 487 | chr7 140475000 140525000 chr7 141975000 142025000 488 | chr7 141775000 141825000 chr7 142775000 142825000 489 | chr7 142375000 142425000 chr7 144175000 144225000 490 | chr8 11625000 11675000 chr8 13025000 13075000 491 | chr8 64325000 64375000 chr8 65325000 65375000 492 | chr8 24575000 24625000 chr8 26575000 26625000 493 | chr8 26125000 26175000 chr8 27025000 27075000 494 | chr8 26675000 26725000 chr8 27775000 27825000 495 | chr8 30625000 30675000 chr8 31625000 31675000 496 | chr8 41475000 41525000 chr8 43075000 43125000 497 | chr8 43175000 43225000 chr8 45175000 45225000 498 | chr8 45125000 45175000 chr8 46025000 46075000 499 | chr8 23075000 23125000 chr8 25075000 25125000 500 | chr8 53675000 53725000 chr8 54575000 54625000 501 | chr8 56375000 56425000 chr8 57475000 57525000 502 | chr8 57175000 57225000 chr8 57975000 58025000 503 | chr8 69725000 69775000 chr8 70925000 70975000 504 | chr8 71475000 71525000 chr8 72475000 72525000 505 | chr8 74375000 74425000 chr8 75775000 75825000 506 | chr8 75275000 75325000 chr8 76075000 76125000 507 | chr8 75375000 75425000 chr8 77275000 77325000 508 | chr8 86625000 86675000 chr8 88225000 88275000 509 | chr8 81175000 81225000 chr8 82875000 82925000 510 | chr8 85675000 85725000 chr8 86675000 86725000 511 | chr8 80375000 80425000 chr8 81175000 81225000 512 | chr8 79575000 79625000 chr8 80775000 80825000 513 | chr8 100725000 100775000 chr8 102125000 102175000 514 | chr8 109775000 109825000 chr8 110675000 110725000 515 | chr8 112825000 112875000 chr8 113625000 113675000 516 | chr8 115175000 115225000 chr8 116275000 116325000 517 | chr8 117475000 117525000 chr8 119575000 119625000 518 | chr8 120525000 120575000 chr8 121725000 121775000 519 | chr8 116475000 116525000 chr8 117775000 117825000 520 | chr9 24925000 24975000 chr9 27425000 27475000 521 | chr9 25975000 26025000 chr9 28275000 28325000 522 | chr9 22825000 22875000 chr9 24925000 24975000 523 | chr9 14175000 14225000 chr9 15675000 15725000 524 | chr9 34425000 34475000 chr9 35925000 35975000 525 | chr9 35275000 35325000 chr9 36875000 36925000 526 | chr9 36375000 36425000 chr9 37875000 37925000 527 | chr9 45075000 45125000 chr9 45875000 45925000 528 | chr9 31975000 32025000 chr9 35275000 35325000 529 | chr9 48875000 48925000 chr9 50875000 50925000 530 | chr9 52225000 52275000 chr9 53125000 53175000 531 | chr9 53575000 53625000 chr9 54975000 55025000 532 | chr9 53825000 53875000 chr9 56325000 56375000 533 | chr9 60975000 61025000 chr9 61875000 61925000 534 | chr9 63075000 63125000 chr9 63875000 63925000 535 | chr9 66025000 66075000 chr9 67025000 67075000 536 | chr9 68025000 68075000 chr9 69225000 69275000 537 | chr9 78825000 78875000 chr9 79825000 79875000 538 | chr9 73025000 73075000 chr9 75225000 75275000 539 | chr9 87875000 87925000 chr9 89375000 89425000 540 | chr9 89125000 89175000 chr9 89925000 89975000 541 | chr9 86825000 86875000 chr9 88525000 88575000 542 | chr9 96625000 96675000 chr9 99325000 99375000 543 | chr9 100225000 100275000 chr9 101325000 101375000 544 | chr9 101275000 101325000 chr9 102475000 102525000 545 | chr9 106375000 106425000 chr9 107575000 107625000 546 | chr9 116575000 116625000 chr9 118075000 118125000 547 | chr9 111375000 111425000 chr9 113675000 113725000 548 | chr9 64125000 64175000 chr9 65125000 65175000 549 | chr9 121725000 121775000 chr9 122925000 122975000 550 | chrX 7425000 7475000 chrX 8525000 8575000 551 | chrX 12425000 12475000 chrX 13425000 13475000 552 | chrX 58525000 58575000 chrX 59425000 59475000 553 | chrX 70325000 70375000 chrX 71625000 71675000 554 | chrX 71825000 71875000 chrX 72825000 72875000 555 | chrX 74425000 74475000 chrX 75325000 75375000 556 | chrX 102025000 102075000 chrX 103225000 103275000 557 | chrX 137325000 137375000 chrX 138825000 138875000 558 | chrX 153725000 153775000 chrX 155025000 155075000 559 | chrX 157775000 157825000 chrX 159075000 159125000 560 | chrX 162825000 162875000 chrX 164225000 164275000 561 | chrX 160875000 160925000 chrX 162375000 162425000 562 | chrX 164625000 164675000 chrX 166325000 166375000 563 | >>>>>>> fd3f9c132494aa3a0536aa90e5f7d71514f59a00 564 | -------------------------------------------------------------------------------- /Fun: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python3.8 2 | import re 3 | import sys 4 | import cli 5 | 6 | if __name__ == '__main__': 7 | cli.cli() 8 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2024 zzdzr 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | 2 | # Fun 3 | ![image](https://zenodo.org/badge/641802007.svg) 4 | **"Fun"** is the algorithm to identify **replication fountains**. The current version is still preliminary and needs further refinement. 5 | 6 | ![image](https://github.com/zzdzr/Fun/blob/master/image/Fun.png) 7 | 8 | # Contents 9 | - [Description](#description) 10 | - [Requirements](#requirements) 11 | - [Usage](#usage) 12 | - [Output](#output) 13 | - [Version](#version) 14 | 15 | # Description 16 | - A high-quality fountain possesses two features: a remarkable **signal-over-noise (SoN)** ratio between the fountain center and its flanking regions and continuous interactions extending along the vertical direction against the diagonal. 17 | - Three major steps are included in the “Fun” pipeline, including **summit identification**, **elongation evaluation** and **end determination**, and further validation with quality control. 18 | - The **.hic** or **.mcool** files of Repli-HiC can be obtained from **Mendeley Data** with https://doi.org/10.17632/4254mwwbhk.1. 19 | 20 | # Requirements 21 | Please ensure that you have already installed the following packages: 22 | ``` 23 | Python(3.8+) packages: numpy(1.23.3), pandas(1.4.1), scipy(1.9.1), click(7.1.2), logging, numba(0.56.2), cooler(0.8.11), bioframe(0.3.3) 24 | ``` 25 | 26 | # Usage 27 | ## Data processing for Repli-HiC 28 | The sequencing library of Repli-HiC requires some preliminary data processing: 29 | - Firstly, the first 9 bases for R1 of the sequencing library need to be removed. 30 | `cutadapt -u 9 -o trimmed_R1.fq input_R1.fq.gz` 31 | 32 | - Then, the **trimLinker** tool should be used to eliminate potential linker sequences within the paired reads. 33 | `trimLinker -m 1 -k 2 -l 16 -o output -n name -A ACGCGATATCTTATC -B AGTCAGATAAGATAT trimmed_R1.fq input_R2.fq.gz` 34 | > trimLinker can be obtained from ChIA-PET2(https://github.com/GuipengLi/ChIA-PET2). 35 | 36 | - Afterwards, the processed sequencing library can be integrated with 4DN Hi-C pipelines for further analysis. 37 | > The 4DN Hi-C data processing pipeline includes alignment, filtering, and matrix aggregation and normalization steps. https://data.4dnucleome.org/resources/data-analysis/hi_c-processing-pipeline 38 | 39 | ## Fountain identification 40 | Generally, there are three major steps in identification of replication fountains. The current version requires step-by-step execution (a more comprehensive version will be updated subsequently, please give me a moment to refine ^_^). 41 | - **Calculate the signal-over-noise (SoN)**. 42 | This calculation module is separated and can be used to calculate the SoN at a given resolution independently. In the present version, you have the ability to define the **search extent** for the sampling box, specify the **width of the sampling box**, and constrain the **offset**. For example, if you want to calculate SoN at 10kb resolution, with search extent at 500kb, padding width at 20kb and offset at 50kb, You can use the following example code. 43 | ``` 44 | Fun calculate-son-score input.mcool::resolutions/10000 --out_dir /output_dir --coverage_ratio 0 --chromsize_path ChromInfo.txt 45 | --ext_length 500000 --padding_width 2 --offset 50000 --integrate True --use_mean True 46 | ``` 47 | 48 | - **Identify potential summits of fountains**. 49 | In current version, we attempt to find summits based on an algorithm from cooltools. This calculation module is based on the results of the previous SoN calculation. Therefore, before executing this module, please ensure that the SoN track can be correctly outputted. 50 | ``` 51 | Fun generate-summits input.mcool::resolutions/10000 --track SoN_10000_merged.bedgraph --out_dir /output_dir 52 | ``` 53 | 54 | - **Identify fountains**. 55 | Before identifying the fountains, please remove the summits that fall into low-quality genomic regions. In this module, you can perform algorithm within a Hi-C matrix of given normalization method and resolution. You can specify the **width of the sampling box, the length of the offset**, and also set the **step size for the sliding layer (--extension_pixels)**, **threshold for the p-value** (--p_value) and **fold change** (--signal_noise_background). (Header of summits.bed should be removed before identifying fountains). 56 | ``` 57 | Fun find-fountains input.mcool::resolutions/10000 --ext_length 500000 --half_width 2 --norm VC_SQRT --region_path Summits_10000_merged.bed 58 | --extension_pixels 10 100 5 --offset 50000 --interval_length 50000 --coverage_ratio 0 --p_value 0.05 --signal_noise_background 1.1 1.2 1.3 1.4 1.5 --output /output_dir/fountains_10kb 59 | ``` 60 | # Output 61 | ### Result Files: 62 | 63 | - ***_.tab**: This file contains identified fountains after quality control. In current version, it contains 14 columns: 64 | 65 | 66 | 67 | |chrom |start|end |name |score |strand |perc_res_list |max_extension |signal_noise_upstream|signal_noise_downstream|signal_noise_average_background| p_values | 68 | |----|-----|-----|----|------|-----|------|------|------|------|----|---| 69 | |chr1|4820000 |4830000|.|1.99 |.|nan, ... , 0.45, 0.45|150|4.60|4.07|4.32|1.1e-08| 70 | 71 | #### Column Explanation: 72 | | Parameter | Description | 73 | | --- | --- | 74 | | **chrom, start, end** | Genomic coordinates of summits. | 75 | | **score** | Signal-over-noise (SoN) score for summits. | 76 | | **perc_res_list** | List containing the proportion of pixels where the central signal region is dominant over the background region at a given distance (The 'nan' values are due to the offset). | 77 | | **max_extension** | The extension length of identified fountains. | 78 | | **signal_noise_upstream** | The ratio of the signal in the central signal region to the signal in the upstream background sampling region. | 79 | | **signal_noise_downstream** | The ratio of the signal in the central signal region to the signal in the downstream background sampling region. | 80 | | **signal_noise_average_background** | The ratio of the signal in the central signal region to the average signal in the upstream and downstream background regions. | 81 | | **p_values** | The p-value obtained from the Kolmogorov-Smirnov (K-S) test performed using the signal from the central region and the average signal from the background region. | 82 | 83 |
84 | 85 | - ***_.bedpe**: This file is converted based on the results of the .tab file 86 | 87 | 88 | | chr1 | x1 | x2 | chr2 | y1 | y2 | 89 | |----|----|----|----|----|----| 90 | |chr1|4675000|4685000|chr1|4975000|4985000| 91 | 92 |
93 | 94 | ### Visualization: 95 | - The current version does not yet offer visualization method, but you can generate the following display through matplotlib. 96 | 97 | 98 | ![image](https://github.com/zzdzr/Fun/blob/master/image/Fountains.png) 99 | 100 | # Version 101 | - Fun v1.0.1 102 | -------------------------------------------------------------------------------- /__pycache__/__init__.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zzdzr/Fun/3fe37b1ffcf647c3c387c8bff128f8c3e4a08331/__pycache__/__init__.cpython-38.pyc -------------------------------------------------------------------------------- /__pycache__/__main__.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zzdzr/Fun/3fe37b1ffcf647c3c387c8bff128f8c3e4a08331/__pycache__/__main__.cpython-38.pyc -------------------------------------------------------------------------------- /cli/__init__.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | import click 3 | import sys 4 | 5 | CONTEXT_SETTING = { 6 | 'help_option_names':['-h', '--help'] 7 | } 8 | 9 | @click.version_option('1.0', '-V', '--version') 10 | @click.group(context_settings = CONTEXT_SETTING) 11 | @click.option('-v', '--verbose', help = 'Verbose test', is_flag=True, default=False) 12 | def cli(verbose): 13 | if verbose: 14 | print('Is verbose') 15 | 16 | from . import ( 17 | calculate_extension_infor, 18 | calculate_SoN, 19 | find_summits 20 | ) 21 | 22 | -------------------------------------------------------------------------------- /cli/__pycache__/__init__.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zzdzr/Fun/3fe37b1ffcf647c3c387c8bff128f8c3e4a08331/cli/__pycache__/__init__.cpython-38.pyc -------------------------------------------------------------------------------- /cli/__pycache__/calculate_SoN.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zzdzr/Fun/3fe37b1ffcf647c3c387c8bff128f8c3e4a08331/cli/__pycache__/calculate_SoN.cpython-38.pyc -------------------------------------------------------------------------------- /cli/__pycache__/calculate_extension_infor.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zzdzr/Fun/3fe37b1ffcf647c3c387c8bff128f8c3e4a08331/cli/__pycache__/calculate_extension_infor.cpython-38.pyc -------------------------------------------------------------------------------- /cli/__pycache__/find_summits.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zzdzr/Fun/3fe37b1ffcf647c3c387c8bff128f8c3e4a08331/cli/__pycache__/find_summits.cpython-38.pyc -------------------------------------------------------------------------------- /cli/__pycache__/measure_strength.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zzdzr/Fun/3fe37b1ffcf647c3c387c8bff128f8c3e4a08331/cli/__pycache__/measure_strength.cpython-38.pyc -------------------------------------------------------------------------------- /cli/__pycache__/test.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zzdzr/Fun/3fe37b1ffcf647c3c387c8bff128f8c3e4a08331/cli/__pycache__/test.cpython-38.pyc -------------------------------------------------------------------------------- /cli/calculate_SoN.py: -------------------------------------------------------------------------------- 1 | import bioframe 2 | import logging 3 | import glob 4 | import click 5 | import os 6 | 7 | from cli import cli 8 | from lib.signal_over_noise import * 9 | from lib.util import * 10 | 11 | 12 | 13 | logging.basicConfig(level=logging.INFO) 14 | logger = logging.getLogger(__name__) 15 | 16 | @cli.command() 17 | @click.argument( 18 | "cool_path", metavar = 'COOL_PATH', 19 | type = str, nargs = 1 20 | ) 21 | @click.option( 22 | "--out_dir", 23 | help = "The output directory of SoNs", 24 | type = str 25 | ) 26 | @click.option( 27 | "--norm", 28 | help = "The normalization method for hic matrix" 29 | "(VC_SQRT, VC and KR normalization)", 30 | default = 'VC_SQRT', 31 | show_default = True, 32 | type = str 33 | ) 34 | @click.option( 35 | "--coverage_ratio", 36 | help = "Given the targeted init bin for plumb," 37 | "if the coverage of bins your collect is lower than " 38 | "this threshold, we consider it as NaNs." 39 | "For sparse matrix, you should consider this argument carefully", 40 | default = 0, 41 | show_default = True, 42 | type = float 43 | ) 44 | @click.option( 45 | "--ext_length", 46 | help = "This is actually the length of sampling box (bp). " 47 | "We recommand that 500Kb for 10kb resolution" 48 | "and 5Mb for 100kb resolution", 49 | default = 500000, 50 | show_default = True, 51 | type = int 52 | ) 53 | @click.option( 54 | "--padding_width", 55 | help = "This parameter is related to the width of sampling and can be understood as follows: " 56 | "If the bin size is 10kb, then setting it to 2 means padding two 10kb bins on each side, " 57 | "thus extending the total to 50kb.", 58 | default = 2, 59 | show_default = True, 60 | type = int 61 | ) 62 | @click.option( 63 | "--offset", 64 | help = "We do not consider length of extension below this threshold " 65 | "The term 'offset' refers to the distance perpendicular to the diagonal; " 66 | "pixels that are below this value in terms of their perpendicular distance " 67 | "from the diagonal do not participate in the computation (bp). ", 68 | default = 20000, 69 | show_default = True, 70 | type = int 71 | ) 72 | @click.option( 73 | "--integrate", 74 | help = "Whether merge .bedgraph track for all chromosmes", 75 | default = True, 76 | show_default = True, 77 | type = bool 78 | ) 79 | @click.option( 80 | "--use_mean", 81 | help = "Use mean for SoN score calculation in pixels from sampling regions else median", 82 | default = False, 83 | show_default = True, 84 | type = bool 85 | ) 86 | @click.option( 87 | "--chromsize_path", 88 | help = "file containing chromsize", 89 | type = str 90 | ) 91 | 92 | 93 | def calculate_SoN_score( 94 | cool_path, out_dir, chromsize_path, norm=False, 95 | coverage_ratio=0.2, ext_length=500000, padding_width=2, 96 | offset=20000, integrate=True, use_mean=False 97 | ): 98 | """ 99 | Calculate signal-over-noise (SoN) score for a specific chromosome. 100 | 101 | Returns: 102 | Dataframe containing SoN scores and corresponding genomic coordinates. 103 | 104 | """ 105 | logger.info('Starting SoN calculation...') 106 | clr, resolution = _load_cooler_object(cool_path) 107 | chromsize = bioframe.read_chromsizes(chromsize_path, natsort=True) 108 | out_dir_path = _create_output_directory(out_dir, resolution) 109 | 110 | for chrom in clr.chromnames: 111 | 112 | logger.info(f'Processing chromosome {chrom}...') 113 | 114 | # calculate SoN score 115 | SoN_track = _calculate_SoN_score( 116 | clr, chrom, norm, ext_length, padding_width, 117 | offset, coverage_ratio, use_mean, chromsize, out_dir_path, resolution 118 | ) 119 | 120 | # output tracks 121 | _write_SoN_tracks( 122 | out_dir_path, chrom, resolution, SoN_track 123 | ) 124 | 125 | logger.info('SoN score calculation completed.') 126 | 127 | if integrate: 128 | logger.info('Merging all chromosome tracks into one file...') 129 | _merge_bedgraph_files(out_dir_path, resolution) 130 | 131 | 132 | def _load_cooler_object(cool_path): 133 | """ 134 | Load cooler object from the given path. 135 | 136 | Args: 137 | cool_path (str): Path to the cooler file. 138 | 139 | Returns: 140 | Cooler object and its resolution. 141 | """ 142 | logger.info(f'Loading cooler object from {cool_path}...') 143 | clr = cooler.Cooler(cool_path) 144 | resolution = clr.binsize 145 | return clr, resolution 146 | 147 | 148 | def _create_output_directory(out_dir, resolution): 149 | """ 150 | Create output directory for SoN tracks. 151 | 152 | Args: 153 | out_dir (str): Base output directory. 154 | resolution (int): Resolution of the cooler file. 155 | 156 | Returns: 157 | Path to the created output directory. 158 | """ 159 | out_dir_path = os.path.join(out_dir, f'SoN_track_{resolution}') 160 | os.makedirs(out_dir_path, exist_ok=True) 161 | logger.info(f'Created directory for SoN tracks: {out_dir_path}') 162 | return out_dir_path 163 | 164 | 165 | def _calculate_SoN_score(clr, chrom, norm, ext_length, padding_width, offset, coverage_ratio, use_mean, chromsize, out_dir_path, resolution): 166 | """ 167 | Calculate signal-over-noise (SoN) score for a specific chromosome. 168 | 169 | """ 170 | 171 | # Check if SoN track already exists 172 | output_path = os.path.join(out_dir_path, f'chr{chrom}_{resolution}_SoN.bedgraph') 173 | if os.path.exists(output_path): 174 | logger.info(f'SoN track for chromosome {chrom} already exists. Skipping...') 175 | 176 | return None 177 | 178 | mat = clr.matrix(balance=norm).fetch(chrom) 179 | SoN_score = calculate_signal_noise_ratio_score( 180 | mat=mat, extension_length=ext_length, 181 | resolution=resolution, half_width=padding_width, 182 | offset=offset, coverage_ratio=coverage_ratio, use_mean=use_mean 183 | ) 184 | 185 | # Handle NaN or infinite values 186 | SoN_score = np.asarray(list(SoN_score)) 187 | SoN_score = np.nan_to_num(SoN_score, nan = 0, posinf=0, neginf=0) 188 | 189 | # Get genomic coordinates 190 | chr_cord_start = [i * clr.binsize for i in range(len(SoN_score))] 191 | chr_cord_end = [(i + 1) * clr.binsize for i in range(len(SoN_score))] 192 | data_dict = { 193 | 'chr': np.repeat('chr' + chrom, len(chr_cord_start)), 194 | 'start': chr_cord_start, 195 | 'end': chr_cord_end, 196 | 'value': SoN_score 197 | } 198 | 199 | SoN_track = align_track_with_chromsize(pd.DataFrame(data_dict), chromsize) 200 | return SoN_track 201 | 202 | def _write_SoN_tracks(out_dir, chrom, resolution, SoN_track): 203 | """ 204 | Write SoN tracks to a bedgraph file. 205 | 206 | Args: 207 | out_dir (str): Output directory for SoN tracks. 208 | chrom (str): Chromosome name. 209 | resolution (int): Resolution of the cooler file. 210 | SoN_track (DataFrame): Dataframe containing SoN scores and genomic coordinates. 211 | """ 212 | output_path = os.path.join(out_dir, f'chr{chrom}_{resolution}_SoN.bedgraph') 213 | 214 | if SoN_track is not None: 215 | 216 | SoN_track.to_csv( 217 | output_path, sep='\t', header=None, index=None 218 | ) 219 | 220 | logger.info(f'SoN track for chromosome {chrom} written to {output_path}') 221 | 222 | def _merge_bedgraph_files(out_dir, resolution): 223 | """ 224 | Merge all .bedgraph files into one. 225 | 226 | Args: 227 | out_dir (str): The directory where the .bedgraph files are stored. 228 | resolution (int): Resolution of the cooler file. 229 | """ 230 | merged_file_name = f'SoN_{resolution}_merged.bedgraph' 231 | merged_file_path = os.path.join(out_dir, merged_file_name) 232 | 233 | # Find all bedgraph files in the output directory 234 | bedgraph_files = glob.glob(os.path.join(out_dir, '*.bedgraph')) 235 | 236 | # Read all bedgraph files and concatenate them 237 | df_list = [ 238 | pd.read_csv(file, sep='\t', header=None) for file in bedgraph_files 239 | ] 240 | 241 | merged_df = pd.concat(df_list, axis=0) 242 | 243 | # Sort by chromosome and start position 244 | merged_df.sort_values(by=[0, 1], inplace=True) 245 | 246 | # Write merged data to a new bedgraph file 247 | merged_df.to_csv(merged_file_path, sep='\t', header=False, index=False) 248 | 249 | logger.info(f'Merged bedgraph file created at {merged_file_path}') -------------------------------------------------------------------------------- /cli/calculate_extension_infor.py: -------------------------------------------------------------------------------- 1 | import bioframe 2 | import cooler 3 | import click 4 | import pandas as pd 5 | from lib.fountain_extension import * 6 | from lib.generate_summits import * 7 | from lib.merge_fountains import * 8 | from lib.quality_filter import * 9 | from lib.trans_to_bedpe import * 10 | from lib.ks_test import * 11 | from cli import cli 12 | 13 | logging.basicConfig(level=logging.INFO) 14 | logger = logging.getLogger(__name__) 15 | 16 | @cli.command() 17 | @click.argument( 18 | "cool_path", metavar='COOL_PATH', 19 | type=str, nargs=1 20 | ) 21 | @click.option( 22 | "--half_width", 23 | help = "This parameter is related to the width of sampling and can be understood as follows: " 24 | "If the bin size is 10kb, then setting it to 2 means padding two 10kb bins on each side, " 25 | "thus extending the total to 50kb.", 26 | type = int 27 | ) 28 | @click.option( 29 | "--ext_length", 30 | help = "This is actually the length of sampling box (bp). " 31 | "We recommand that 500Kb for 10kb resolution" 32 | "and 5Mb for 100kb resolution", 33 | type = int 34 | ) 35 | @click.option( 36 | "--norm", 37 | help = "The normalization method for hic matrix" 38 | "(VC_SQRT, VC and KR normalization... based on your Cooler object)", 39 | default = 'VC_SQRT', 40 | show_default = True, 41 | type = str 42 | ) 43 | @click.option( 44 | "--region_path", 45 | help = "Absolute path for fountains summits", 46 | type = str 47 | ) 48 | @click.option( 49 | "--extension_pixels", 50 | help = "Array of locations we used to calculate dominance in extension. " 51 | "briefly, we just need to calculate the dominance at the specific pixel's position (for faster speed) " 52 | "This param needs further explanation in future version...", 53 | nargs = 3, 54 | type = int 55 | ) 56 | @click.option( 57 | "--offset", 58 | help = "We do not consider length of extension below this threshold " 59 | "The term 'offset' refers to the distance perpendicular to the diagonal; " 60 | "pixels that are below this value in terms of their perpendicular distance " 61 | "from the diagonal do not participate in the computation (bp). ", 62 | default = 50000, 63 | show_default = True, 64 | type = int 65 | ) 66 | @click.option( 67 | "--interval_length", 68 | help = "This param determines the length (bp) of sliding sheet containing " 69 | "multiple layers.", 70 | type = int 71 | ) 72 | @click.option( 73 | "--coverage_ratio", 74 | help = "Given the targeted init bin for plumb," 75 | "if the coverage of bins your collect is lower than " 76 | "this threshold, we consider it as NaNs." 77 | "For sparse matrix, you should consider this argument carefully", 78 | type = float 79 | ) 80 | @click.option( 81 | "--output", 82 | help = "The absolute file path of output results", 83 | type = str 84 | ) 85 | @click.option( 86 | "--p_value", 87 | help = "The threshold of p-value for K-S test", 88 | default=0.05, 89 | show_default=True, 90 | type = float 91 | ) 92 | @click.option( 93 | "--signal_noise_background", 94 | help = "The threshold of SoN(fold change) for fountains", 95 | nargs=5, 96 | default=1.0, 97 | show_default=True, 98 | type = float 99 | ) 100 | @click.option( 101 | "--max_merge_distance", 102 | help = "The maximum length we use to merge two close fountains", 103 | default=50000, 104 | show_default=True, 105 | type = int 106 | ) 107 | 108 | def find_fountains( 109 | cool_path, half_width, ext_length, 110 | region_path, extension_pixels, offset, 111 | interval_length, coverage_ratio, output, norm=False, 112 | p_value = 0.05, signal_noise_background = 1.0, 113 | max_merge_distance = 20000, 114 | ): 115 | """ 116 | Find fountains based on identified summits. 117 | 118 | """ 119 | 120 | logger.info('Starting finding fountains...') 121 | 122 | # load Cooler object 123 | clr = cooler.Cooler(cool_path) 124 | 125 | # Determine resolution and load regions of summits 126 | resolution = clr.binsize 127 | region = bioframe.read_table( 128 | region_path, schema='bed' 129 | ) 130 | 131 | # Bin array based on extension pixels (briefly, we just need to calculate the dominance at the specific pixel's position (for faster speed)） 132 | bin_array = np.arange( 133 | extension_pixels[0], extension_pixels[1], extension_pixels[2] 134 | ) 135 | 136 | # Perform plumb calculation, get length and fold change of fountains 137 | logger.info('Calculate length of fountains and SoN (fold change)...') 138 | df = plumb( 139 | clr, half_width = half_width, extension_length=ext_length, 140 | norm=norm, regions=region, bin_array=bin_array, offset=offset, 141 | interval_length=interval_length, coverage_ratio = coverage_ratio 142 | ) 143 | 144 | df = calculate_fountain_SoN( 145 | clr, df, norm=norm, 146 | half_width = half_width, 147 | coverage_ratio=coverage_ratio, 148 | offset = offset 149 | ) 150 | 151 | # Perform K-S test 152 | logger.info('Perform K-S test...') 153 | df = make_ks_test( 154 | clr, regions=df, half_width = half_width, 155 | coverage_ratio=coverage_ratio, norm=norm, 156 | offset = offset 157 | ) 158 | 159 | # Filter based on extension, p-value, and signal noise 160 | logger.info('Perform filter...') 161 | ext_bool = filter_extension(df) 162 | pvalue_bool = df['p_value'] < p_value 163 | 164 | for val in signal_noise_background: 165 | 166 | signal_bool = df['signal_noise_average_background'] > val 167 | df_tmp = df[(ext_bool & pvalue_bool & signal_bool)] 168 | df_tmp = merge_fountains(df_tmp.reset_index(drop=True), max_distance=max_merge_distance) 169 | output_tmp1 = f"{output}_{val}.tab" 170 | df_tmp.to_csv(output_tmp1, header=True, index=None, sep='\t') 171 | 172 | output_tmp2 = f"{output}_{val}.bedpe" 173 | bedpe = dataframe_to_bedpe(df_tmp, resolution=resolution) 174 | bedpe.to_csv(output_tmp2, header=True, index=None, sep='\t') 175 | 176 | logger.info('Complete!') 177 | -------------------------------------------------------------------------------- /cli/find_summits.py: -------------------------------------------------------------------------------- 1 | import os 2 | import cooler 3 | import click 4 | import logging 5 | 6 | import numpy as np 7 | import pandas as pd 8 | 9 | from cli import cli 10 | from lib.find_peaks import find_peak_prominence 11 | 12 | logging.basicConfig(level=logging.INFO) 13 | logger = logging.getLogger(__name__) 14 | 15 | @cli.command() 16 | @click.argument( 17 | "cool_path", metavar='COOL_PATH', 18 | type=str, nargs=1 19 | ) 20 | @click.option( 21 | "--track", 22 | help = "The absolute path of SoN tracks for all chroms", 23 | type = str 24 | ) 25 | @click.option( 26 | "--out_dir", 27 | help = "The absolute path for output directory", 28 | type = str 29 | ) 30 | 31 | def generate_summits(cool_path, track, out_dir): 32 | """ 33 | Find summits based on SoN 34 | 35 | """ 36 | 37 | # load cooler and SoN track 38 | logger.info('Starting Summits detection...') 39 | clr = cooler.Cooler(cool_path) 40 | track_data = _load_track_data(track) 41 | 42 | # suffix 43 | resolution = clr.binsize 44 | suffix = f'_{resolution // 1000}kb.bed' 45 | 46 | out_dir = os.path.join(out_dir, 'SoN_summits/') 47 | os.makedirs(out_dir, exist_ok=True) 48 | 49 | for chrom in clr.chromnames: 50 | logger.info(f'Processing chromosome {chrom}...') 51 | _process_chromosome_data('chr' + chrom, track_data, out_dir, suffix) 52 | 53 | _merge_summits(out_dir, resolution) 54 | 55 | 56 | def _load_track_data(track_path): 57 | """ 58 | Load track data from the given path. 59 | 60 | """ 61 | track_data = pd.read_table( 62 | track_path, header=None, sep='\t', names = ['chrom', 'start', 'end', 'SoN'] 63 | ) 64 | 65 | return track_data 66 | 67 | 68 | def _process_chromosome_data(chrom, track, out_dir, suffix): 69 | """ 70 | Process track data for a specific chromosome and write summits to file. 71 | 72 | """ 73 | 74 | SoN_df = track[track.loc[:, 'chrom'] == chrom].copy() 75 | SoN_df.loc[:, 'SoN'] = SoN_df.loc[:, 'SoN'].clip(lower=0) 76 | 77 | # Get positions of summits 78 | poss, _ = find_peak_prominence(SoN_df.loc[:, 'SoN'].values) 79 | 80 | chr_cord_start = SoN_df.loc[:, 'start'].values[poss] 81 | chr_cord_end = SoN_df.loc[:, 'end'].values[poss] 82 | names = np.repeat('.', len(poss)) 83 | strands = np.repeat('.', len(poss)) 84 | 85 | # Get SoN scores 86 | SoN_values = SoN_df.loc[:, 'SoN'].values[poss] 87 | 88 | data_dict = { 89 | 'chr': np.repeat(chrom, len(poss)), 90 | 'start': chr_cord_start, 91 | 'end': chr_cord_end, 92 | 'name': names, 93 | 'SoN': SoN_values, 94 | 'strand': strands 95 | } 96 | 97 | df = pd.DataFrame(data_dict) 98 | df.to_csv( 99 | os.path.join(out_dir, chrom + suffix), 100 | sep='\t', header=True, index=None 101 | ) 102 | 103 | def _merge_summits(out_dir, resolution): 104 | """ 105 | Merge individual summit files into one. 106 | 107 | """ 108 | merged_file_name = f'Summits_{resolution}_merged.bed' 109 | merged_file_path = os.path.join(out_dir, merged_file_name) 110 | 111 | files = [f for f in os.listdir(out_dir) if f.endswith('.bed')] 112 | first = True 113 | 114 | if not os.path.exists(merged_file_path): 115 | with open(merged_file_path, 'w') as wfd: 116 | for f in files: 117 | file_path = os.path.join(out_dir, f) 118 | 119 | with open(file_path, 'r') as fd: 120 | if first: 121 | columns = next(fd) 122 | wfd.write(columns) 123 | first = False 124 | else: 125 | next(fd) 126 | 127 | for line in fd: 128 | wfd.write(line) 129 | 130 | else: 131 | logger.info('merged summits already exist, skip...') 132 | 133 | -------------------------------------------------------------------------------- /image/.DS_Store: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zzdzr/Fun/3fe37b1ffcf647c3c387c8bff128f8c3e4a08331/image/.DS_Store -------------------------------------------------------------------------------- /image/Fountains.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zzdzr/Fun/3fe37b1ffcf647c3c387c8bff128f8c3e4a08331/image/Fountains.png -------------------------------------------------------------------------------- /image/Fun.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zzdzr/Fun/3fe37b1ffcf647c3c387c8bff128f8c3e4a08331/image/Fun.png -------------------------------------------------------------------------------- /lib/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zzdzr/Fun/3fe37b1ffcf647c3c387c8bff128f8c3e4a08331/lib/__init__.py -------------------------------------------------------------------------------- /lib/__pycache__/__init__.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zzdzr/Fun/3fe37b1ffcf647c3c387c8bff128f8c3e4a08331/lib/__pycache__/__init__.cpython-38.pyc -------------------------------------------------------------------------------- /lib/__pycache__/diagonal_plumb.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zzdzr/Fun/3fe37b1ffcf647c3c387c8bff128f8c3e4a08331/lib/__pycache__/diagonal_plumb.cpython-38.pyc -------------------------------------------------------------------------------- /lib/__pycache__/find_peaks.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zzdzr/Fun/3fe37b1ffcf647c3c387c8bff128f8c3e4a08331/lib/__pycache__/find_peaks.cpython-38.pyc -------------------------------------------------------------------------------- /lib/__pycache__/fountain_extension.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zzdzr/Fun/3fe37b1ffcf647c3c387c8bff128f8c3e4a08331/lib/__pycache__/fountain_extension.cpython-38.pyc -------------------------------------------------------------------------------- /lib/__pycache__/generate_summits.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zzdzr/Fun/3fe37b1ffcf647c3c387c8bff128f8c3e4a08331/lib/__pycache__/generate_summits.cpython-38.pyc -------------------------------------------------------------------------------- /lib/__pycache__/ks_test.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zzdzr/Fun/3fe37b1ffcf647c3c387c8bff128f8c3e4a08331/lib/__pycache__/ks_test.cpython-38.pyc -------------------------------------------------------------------------------- /lib/__pycache__/merge_fountains.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zzdzr/Fun/3fe37b1ffcf647c3c387c8bff128f8c3e4a08331/lib/__pycache__/merge_fountains.cpython-38.pyc -------------------------------------------------------------------------------- /lib/__pycache__/quality_filter.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zzdzr/Fun/3fe37b1ffcf647c3c387c8bff128f8c3e4a08331/lib/__pycache__/quality_filter.cpython-38.pyc -------------------------------------------------------------------------------- /lib/__pycache__/rotation.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zzdzr/Fun/3fe37b1ffcf647c3c387c8bff128f8c3e4a08331/lib/__pycache__/rotation.cpython-38.pyc -------------------------------------------------------------------------------- /lib/__pycache__/signal_over_noise.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zzdzr/Fun/3fe37b1ffcf647c3c387c8bff128f8c3e4a08331/lib/__pycache__/signal_over_noise.cpython-38.pyc -------------------------------------------------------------------------------- /lib/__pycache__/test.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zzdzr/Fun/3fe37b1ffcf647c3c387c8bff128f8c3e4a08331/lib/__pycache__/test.cpython-38.pyc -------------------------------------------------------------------------------- /lib/__pycache__/trans_to_bedpe.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zzdzr/Fun/3fe37b1ffcf647c3c387c8bff128f8c3e4a08331/lib/__pycache__/trans_to_bedpe.cpython-38.pyc -------------------------------------------------------------------------------- /lib/__pycache__/util.cpython-38.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/zzdzr/Fun/3fe37b1ffcf647c3c387c8bff128f8c3e4a08331/lib/__pycache__/util.cpython-38.pyc -------------------------------------------------------------------------------- /lib/diagonal_plumb.py: -------------------------------------------------------------------------------- 1 | import copy 2 | import numba 3 | import cooler 4 | import warnings 5 | import numpy as np 6 | import matplotlib.pyplot as plt 7 | 8 | @numba.jit(nopython=True) 9 | def plumb_numbda(half_width, init_bin, extension_length, n_bins, offset, resolution): 10 | ''' 11 | 12 | Notes: 13 | We use numba to accelerate the loops, therefore, 14 | we could fastly generate the coordinates we used to pileup 15 | 16 | You should mention that the init_bin should not exceed the boundary of matrix, 17 | it will result some unknown errors. 18 | 19 | * If the extension length < resolution, we only obtain the initial value for the first pixel (init pixel) 20 | * If exceed the boundary, the element is empty 21 | ''' 22 | 23 | if np.isnan(extension_length): 24 | raise ValueError('nan extension length') 25 | 26 | extension_bins = (extension_length // resolution) * 2 27 | 28 | if offset != 0: 29 | offset_bins = (offset // resolution) * 2 + 1 30 | else: 31 | offset_bins = 0 32 | 33 | init_row_idx, init_col_idx = np.arange(init_bin - half_width, init_bin + half_width + 1), \ 34 | np.arange(init_bin - half_width, init_bin + half_width + 1) 35 | 36 | assert offset_bins < extension_bins+1, \ 37 | 'The offset should not exceed length of extension' 38 | 39 | for i in range(offset_bins, extension_bins + 1): 40 | if i % 2 == 0: 41 | row_idx = init_row_idx - i // 2 42 | col_idx = init_col_idx + i // 2 43 | 44 | else: 45 | row_idx = row_idx[:-1] if len(row_idx) > 1 else row_idx 46 | col_idx = col_idx[:-1] + 1 if len(col_idx) > 1 else col_idx + 1 47 | 48 | # Do not exceed the boundaries 49 | cond = (row_idx >= 0) & (col_idx <= n_bins - 1) 50 | row_idx = row_idx[cond] 51 | col_idx = col_idx[cond] 52 | 53 | yield row_idx, col_idx 54 | 55 | 56 | @numba.jit(nopython=True) 57 | def nb_sum(x): 58 | sum_ = 0 59 | for i in range(len(x)): 60 | sum_ += x[i] 61 | return sum_ 62 | 63 | def plumb_sum(mat, half_width, init_bin, extension_length, resolution, offset): 64 | ''' 65 | calculate sum of interactions in sampling box at target bin 66 | 67 | Parameters 68 | ---------- 69 | mat: ndarray object 70 | hic matrix 71 | 72 | half_width: int object 73 | number of bins of padding regions for its center 74 | 75 | extension_length: int object 76 | the length of extension (bp) 77 | 78 | Returns 79 | ------- 80 | val : float object 81 | sum of interaction at each distance 82 | ''' 83 | 84 | for row_idx, col_idx in plumb_numbda( 85 | half_width=half_width, 86 | init_bin=init_bin, 87 | extension_length=extension_length, 88 | n_bins=mat.shape[0], 89 | offset=offset, 90 | resolution=resolution 91 | ): 92 | 93 | if row_idx.size == 0 or col_idx.size == 0: 94 | val = np.nan 95 | else: 96 | val = np.nansum(mat[row_idx, col_idx]) 97 | 98 | yield val 99 | 100 | def global_diag_plumb_sum(mat, half_width, extension_length, offset): 101 | ''' 102 | This function can perform "plumb_sum" at all bins along the matrix 103 | 104 | ''' 105 | for _ in range(n_bins): 106 | diag_plumb_val = np.asarray([ 107 | i for i in plumb_sum(mat, half_width, _, extension_length, offset) 108 | ]) 109 | 110 | yield diag_plumb_val 111 | 112 | def plumb_layer_values(mat, half_width, init_bin, extension_length, resolution, offset): 113 | ''' 114 | calculate sum of interactions in sampling box at target bin 115 | 116 | Parameters 117 | ---------- 118 | mat: ndarray object 119 | hic matrix 120 | 121 | half_width: int object 122 | number of bins of padding regions for its center 123 | 124 | extension_length: int object 125 | the length of extension (bp) 126 | 127 | Returns 128 | ------- 129 | val : float object 130 | sum of interaction at each distance 131 | ''' 132 | 133 | for row_idx, col_idx in plumb_numbda( 134 | half_width=half_width, 135 | init_bin=init_bin, 136 | extension_length=extension_length, 137 | n_bins=mat.shape[0], 138 | offset=offset, 139 | resolution=resolution 140 | ): 141 | 142 | layers = [] 143 | if row_idx.size == 0 or col_idx.size == 0: 144 | val = np.nan 145 | else: 146 | val = mat[row_idx, col_idx] 147 | 148 | layers.append(val) 149 | 150 | return layers 151 | 152 | 153 | def plumb_mean(mat, half_width, init_bin, extension_length, resolution, offset): 154 | ''' 155 | calculate sum of interactions in sampling box at target bin 156 | 157 | Parameters 158 | ---------- 159 | mat: ndarray object 160 | hic matrix 161 | 162 | half_width: int object 163 | number of bins of padding regions for its center 164 | 165 | extension_length: int object 166 | the length of extension (bp) 167 | 168 | Returns 169 | ------- 170 | val : float object 171 | sum of interaction at each distance 172 | ''' 173 | 174 | for row_idx, col_idx in plumb_numbda( 175 | half_width=half_width, 176 | init_bin=init_bin, 177 | extension_length=extension_length, 178 | n_bins=mat.shape[0], 179 | offset=offset, 180 | resolution=resolution 181 | ): 182 | 183 | if row_idx.size == 0 or col_idx.size == 0: 184 | val = np.nan 185 | else: 186 | val = np.nanmean(mat[row_idx, col_idx]) 187 | 188 | yield val -------------------------------------------------------------------------------- /lib/find_peaks.py: -------------------------------------------------------------------------------- 1 | def find_peak_prominence(arr, max_dist=None): 2 | """Find the local maxima of an array and their prominence. 3 | The prominence of a peak is defined as the maximal difference between the 4 | height of the peak and the lowest point in the range until a higher peak. 5 | Parameters 6 | ---------- 7 | arr : array_like 8 | max_dist : int 9 | If specified, the distance to the adjacent higher peaks is limited 10 | by `max_dist`. 11 | Returns 12 | ------- 13 | loc_max_poss : numpy.array 14 | The positions of local maxima of a given array. 15 | proms : numpy.array 16 | The prominence of the detected maxima. 17 | """ 18 | import numpy as np 19 | import warnings 20 | 21 | arr = np.asarray(arr) 22 | n = len(arr) 23 | max_dist = len(arr) if max_dist is None else int(max_dist) 24 | 25 | # Finding all local minima and maxima (i.e. points the are lower/higher than 26 | # both immediate non-nan neighbors). 27 | arr_nonans = arr[~np.isnan(arr)] 28 | idxs_nonans2idx = np.arange(arr.size)[~np.isnan(arr)] 29 | 30 | with warnings.catch_warnings(): 31 | warnings.simplefilter("ignore", RuntimeWarning) 32 | 33 | is_min_left = np.r_[False, arr_nonans[:-1] > arr_nonans[1:]] 34 | is_min_right = np.r_[arr_nonans[:-1] < arr_nonans[1:], False] 35 | is_loc_min = is_min_left & is_min_right 36 | loc_min_poss = np.where(is_loc_min)[0] 37 | loc_min_poss = idxs_nonans2idx[loc_min_poss] 38 | 39 | is_max_left = np.r_[False, arr_nonans[:-1] < arr_nonans[1:]] 40 | is_max_right = np.r_[arr_nonans[:-1] > arr_nonans[1:], False] 41 | is_loc_max = is_max_left & is_max_right 42 | loc_max_poss = np.where(is_loc_max)[0] 43 | loc_max_poss = idxs_nonans2idx[loc_max_poss] 44 | 45 | # For each maximum, find the position of a higher peak on the left and 46 | # on the right. If there are no higher peaks within the `max_dist` range, 47 | # just use the position `max_dist` away. 48 | left_maxs = -1 * np.ones(len(loc_max_poss), dtype=np.int64) 49 | right_maxs = -1 * np.ones(len(loc_max_poss), dtype=np.int64) 50 | 51 | for i, pos in enumerate(loc_max_poss): 52 | for j in range(pos - 1, -1, -1): 53 | if (arr[j] > arr[pos]) or (pos - j > max_dist): 54 | left_maxs[i] = j 55 | break 56 | 57 | for j in range(pos + 1, n): 58 | if (arr[j] > arr[pos]) or (j - pos > max_dist): 59 | right_maxs[i] = j 60 | break 61 | 62 | # Find the prominence of each peak with respect of the lowest point 63 | # between the peak and the adjacent higher peaks, on the left and the right 64 | # separately. 65 | left_max_proms = np.array( 66 | [ 67 | ( 68 | arr[pos] - np.nanmin(arr[left_maxs[i] : pos]) 69 | if (left_maxs[i] >= 0) 70 | else np.nan 71 | ) 72 | for i, pos in enumerate(loc_max_poss) 73 | ] 74 | ) 75 | 76 | right_max_proms = np.array( 77 | [ 78 | ( 79 | arr[pos] - np.nanmin(arr[pos : right_maxs[i]]) 80 | if (right_maxs[i] >= 0) 81 | else np.nan 82 | ) 83 | for i, pos in enumerate(loc_max_poss) 84 | ] 85 | ) 86 | 87 | # In 1D, the topographic definition of the prominence of a peak reduces to 88 | # the minimum of the left-side and right-side prominence. 89 | 90 | with warnings.catch_warnings(): 91 | warnings.simplefilter("ignore", RuntimeWarning) 92 | 93 | max_proms = np.nanmin(np.vstack([left_max_proms, right_max_proms]), axis=0) 94 | 95 | # The global maximum, by definition, does not have higher peaks around it and 96 | # thus its prominence is explicitly defined with respect to the lowest local 97 | # minimum. This issue arises only if max_dist was not specified, otherwise 98 | # the prominence of the global maximum is already calculated with respect 99 | # to the lowest point within the `max_dist` range. 100 | # If no local minima are within the `max_dist` range, just use the 101 | # lowest point. 102 | global_max_mask = (left_maxs == -1) & (right_maxs == -1) 103 | if (global_max_mask).sum() > 0: 104 | global_max_idx = np.where(global_max_mask)[0][0] 105 | global_max_pos = loc_max_poss[global_max_idx] 106 | neighbor_loc_mins = (loc_min_poss >= global_max_pos - max_dist) & ( 107 | loc_min_poss < global_max_pos + max_dist 108 | ) 109 | if np.any(neighbor_loc_mins): 110 | max_proms[global_max_idx] = arr[global_max_pos] - np.nanmin( 111 | arr[loc_min_poss[neighbor_loc_mins]] 112 | ) 113 | else: 114 | max_proms[global_max_idx] = arr[global_max_pos] - np.nanmin( 115 | arr[max(global_max_pos - max_dist, 0) : global_max_pos + max_dist] 116 | ) 117 | 118 | return loc_max_poss, max_proms -------------------------------------------------------------------------------- /lib/fountain_extension.py: -------------------------------------------------------------------------------- 1 | from .signal_over_noise import * 2 | import logging 3 | 4 | # logging.basicConfig(format='%(levelname)s:%(funcName)s:%(message)s', level=logging.DEBUG) 5 | def find_maximum_extension(signal_track, resolution, interval_length = 50000, threshold = 0.5): 6 | 7 | if not isinstance(signal_track, np.ndarray): 8 | raise TypeError('Invalid signal track, please use ndarray!') 9 | 10 | n_bins = (interval_length // resolution) * 2 - 1 11 | 12 | 13 | #half_width = interval_length // 2 // resolution * 2 14 | half_width = interval_length//resolution - 1 15 | 16 | for i in range(0, len(signal_track)): 17 | 18 | if i < half_width or i + half_width > len(signal_track) - 1: 19 | n_dominance = np.nan 20 | 21 | else: 22 | signal = signal_track[i - half_width: i + half_width + 1] 23 | n_dominance = signal[signal <= 0].size 24 | 25 | # we could stop at the bin i 26 | if n_dominance / n_bins >= threshold: 27 | 28 | # then we should find the bin with max value 29 | #max_idx = np.argmax(signal_track[i - half_width: i+1]) 30 | 31 | max_idx = np.argmax(signal_track[i-half_width:i+half_width+1]) 32 | 33 | obtained_idx = i - n_bins // 2 + max_idx 34 | 35 | return obtained_idx 36 | 37 | return n_bins 38 | 39 | 40 | def calculate_dominance(signal_track, bin_array, threshold = 0): 41 | 42 | if bin_array[0] < 1: 43 | raise ValueError('The first index should greater than 0, otherwise empty') 44 | 45 | if isinstance(signal_track, np.ndarray): 46 | percent_list = [] 47 | # logging.debug('The shape of signal_track is %d' % signal_track.shape) 48 | # logging.debug('The length of bin array is %d' % bin_array.shape) 49 | 50 | if bin_array.size > signal_track.size: 51 | raise ValueError( 52 | 'The index in bin_array should not exceed the bound of ndarray' 53 | ) 54 | 55 | for idx in bin_array: 56 | signal = signal_track[:idx] 57 | percent = signal[signal > threshold].size / signal.size 58 | percent_list.append(percent) 59 | 60 | else: 61 | raise TypeError('Signal track must be type of ndarray!') 62 | 63 | percent_list = np.asarray(percent_list) 64 | 65 | if bin_array[0] > 1: 66 | percent_list = np.append(np.repeat(np.nan, bin_array[0] - 1), percent_list) 67 | 68 | return percent_list 69 | 70 | def center_background_plumb( 71 | mat, half_width, extension_length, init_bin, resolution, 72 | offset, bin_array, coverage_ratio = 0.2, interval_length = 50000, threshold = 0.5 73 | ): 74 | 75 | tkg_plumb, up_bkg, down_bkg = set_sampling_box( 76 | mat = mat, half_width = half_width, extension_length = extension_length, 77 | offset = offset, init_bin = init_bin, coverage_ratio=coverage_ratio, resolution=resolution 78 | ) 79 | 80 | if np.all( 81 | [isinstance(i, np.ndarray) for i in [up_bkg, down_bkg, tkg_plumb]] 82 | ): 83 | 84 | bkg_ave = np.nanmean( 85 | [up_bkg, down_bkg], axis = 0 86 | ) 87 | 88 | tkg_bkg_subtract = tkg_plumb - bkg_ave 89 | maximum_extension = find_maximum_extension( 90 | tkg_bkg_subtract, resolution = resolution, 91 | interval_length = interval_length, threshold = threshold 92 | ) 93 | 94 | percent_list = calculate_dominance( 95 | tkg_bkg_subtract, bin_array = bin_array 96 | ) 97 | 98 | else: 99 | return np.nan, np.nan 100 | 101 | return maximum_extension, percent_list 102 | 103 | def center_area_plumb_sum( 104 | mat, half_width, extension_length, 105 | bin_idx, offset, resolution, coverage_ratio = None 106 | ): 107 | 108 | if coverage_ratio is None: 109 | raise ValueError('Empty coverage ratio.') 110 | 111 | target_plumb_val = np.asarray( 112 | [i for i in plumb_sum( 113 | mat = mat, 114 | half_width = half_width, 115 | init_bin = bin_idx, extension_length = extension_length, 116 | resolution = resolution, offset = offset 117 | )] 118 | ) 119 | 120 | if len(target_plumb_val) >= 1: 121 | cov_ratio = calculate_coverage(target_plumb_val) 122 | 123 | else: 124 | cov_ratio = 0 125 | 126 | if cov_ratio <= coverage_ratio: 127 | target_plumb_val = np.nan 128 | 129 | 130 | return target_plumb_val 131 | 132 | def set_sampling_box( 133 | mat, half_width, extension_length, init_bin, resolution, 134 | offset, coverage_ratio = 0.2 135 | ): 136 | 137 | tkg_plumb = center_area_plumb_sum( 138 | mat=mat, half_width=half_width, extension_length=extension_length, 139 | offset=offset, bin_idx=init_bin, coverage_ratio=coverage_ratio, resolution=resolution 140 | ) 141 | 142 | up_bkg = set_background( 143 | mat=mat, half_width=half_width, extension_length=extension_length, 144 | offset=offset, bin_idx=init_bin, orientation='upstream', 145 | coverage_ratio=coverage_ratio, resolution=resolution 146 | ) 147 | 148 | down_bkg = set_background( 149 | mat=mat, half_width=half_width, extension_length=extension_length, 150 | offset=offset, bin_idx=init_bin, orientation='downstream', 151 | coverage_ratio=coverage_ratio, resolution=resolution 152 | ) 153 | 154 | return tkg_plumb, up_bkg, down_bkg 155 | 156 | def calculate_fountain_SoN( 157 | clr, regions, half_width, 158 | coverage_ratio, norm, offset 159 | ): 160 | 161 | regions = regions.copy() 162 | regions = regions.sort_values(by = 'chrom').reset_index(drop = True) 163 | 164 | if not set( 165 | ['chrom', 'start', 'end', 'max_extension'] 166 | ).issubset(regions.columns): 167 | 168 | raise TypeError( 169 | 'Invalid dataframe \n ' 170 | 'columns: "chrom", "start", "end", "max_extension" are needed' 171 | ) 172 | 173 | resolution = clr.binsize 174 | chrom_list = [] 175 | upstream_signal_noise_ratio_list = [] 176 | downstream_signal_noise_ratio_list = [] 177 | ave_bkg_signal_noise_ratio_list = [] 178 | 179 | for index, row in regions.iterrows(): 180 | 181 | chrom = row['chrom'][3:] 182 | init_bin = (row['end'] + row['start']) // resolution // 2 183 | # 20230411 revise 184 | extension_length = row['max_extension'] * 1000 185 | 186 | if np.isnan(extension_length) or \ 187 | offset >= extension_length: 188 | tkg_plumb, up_bkg, down_bkg = np.nan, np.nan, np.nan 189 | 190 | else: 191 | 192 | if not chrom in chrom_list: 193 | chrom_list.append(chrom) 194 | mat = clr.matrix(balance = norm).fetch(chrom) 195 | 196 | tkg_plumb, up_bkg, down_bkg = set_sampling_box( 197 | mat=mat, half_width=half_width, 198 | extension_length=extension_length, offset=offset, 199 | init_bin=init_bin, resolution=resolution, coverage_ratio=coverage_ratio 200 | ) 201 | 202 | # calculate median interaction in fountain and its signal-over-noise 203 | # for central area and background areas 204 | if np.all( 205 | [isinstance(i, np.ndarray) for i in [up_bkg, down_bkg, tkg_plumb]] 206 | ): 207 | bkg_ave = np.nanmean( 208 | [up_bkg, down_bkg], axis=0 209 | ) 210 | 211 | tkg_plumb_sum = np.nansum(tkg_plumb) 212 | bkg_ave_sum = np.nansum(bkg_ave) 213 | bkg_upstream_sum = np.nansum(up_bkg) 214 | bkg_downstream_sum = np.nansum(down_bkg) 215 | 216 | # calculate signal-noise ratio for average background 217 | signal_background_ratio = tkg_plumb_sum / bkg_ave_sum 218 | 219 | # calculate signal-noise ratio for upstream background 220 | signal_upstream_background_ratio = tkg_plumb_sum / bkg_upstream_sum 221 | 222 | # calculate signal-noise ratio for downstream background 223 | signal_downstream_background_ratio = tkg_plumb_sum / bkg_downstream_sum 224 | 225 | # ratio should not be inf 226 | if np.isinf(signal_background_ratio): 227 | signal_background_ratio = np.nan 228 | 229 | if np.isinf(signal_upstream_background_ratio): 230 | signal_upstream_background_ratio = np.nan 231 | 232 | if np.isinf(signal_downstream_background_ratio): 233 | signal_downstream_background_ratio = np.nan 234 | 235 | 236 | # calculate median of interactions of fountain 237 | #tkg_plumb_median = np.nanmedian(tkg_plumb_sum) 238 | # revised 20230411 239 | tkg_plumb_median = np.nanmedian(tkg_plumb) 240 | 241 | else: 242 | tkg_plumb_sum = np.nan 243 | signal_background_ratio = np.nan 244 | signal_upstream_background_ratio = np.nan 245 | signal_downstream_background_ratio = np.nan 246 | tkg_plumb_median = np.nan 247 | 248 | upstream_signal_noise_ratio_list.append( 249 | signal_upstream_background_ratio 250 | ) 251 | 252 | downstream_signal_noise_ratio_list.append( 253 | signal_downstream_background_ratio 254 | ) 255 | 256 | ave_bkg_signal_noise_ratio_list.append( 257 | signal_background_ratio 258 | ) 259 | 260 | 261 | regions['signal_noise_upstream'] = upstream_signal_noise_ratio_list 262 | regions['signal_noise_downstream'] = downstream_signal_noise_ratio_list 263 | regions['signal_noise_average_background'] = ave_bkg_signal_noise_ratio_list 264 | 265 | 266 | return regions 267 | 268 | def plumb( 269 | clr, half_width, extension_length, norm, 270 | regions, bin_array, offset, coverage_ratio, 271 | interval_length = 50000, threshold = 0.5 272 | ): 273 | 274 | regions = regions.copy() 275 | regions = regions.sort_values(by = 'chrom').reset_index(drop = True) 276 | 277 | if not set(['chrom', 'start', 'end']).issubset(regions.columns): 278 | raise TypeError('Invalid dataframe') 279 | 280 | resolution = clr.binsize 281 | chrom_list = [] 282 | perc_res_list = [] 283 | max_ext_list = [] 284 | 285 | for index, row in regions.iterrows(): 286 | chrom = row['chrom'][3:] 287 | init_bin = (row['end'] + row['start']) // resolution // 2 288 | 289 | if not chrom in chrom_list: 290 | chrom_list.append(chrom) 291 | mat = clr.matrix(balance=norm).fetch(chrom) 292 | 293 | max_ext, perc_list = center_background_plumb( 294 | mat = mat, half_width=half_width, 295 | extension_length=extension_length, init_bin=init_bin, 296 | offset = offset, coverage_ratio = coverage_ratio, resolution=resolution, 297 | bin_array = bin_array, interval_length=interval_length, threshold = threshold 298 | ) 299 | 300 | try: 301 | perc_list = list(perc_list) 302 | except: 303 | perc_list = list(np.zeros_like(bin_array)) 304 | 305 | perc_res_list.append(perc_list) 306 | 307 | if not np.isnan(max_ext): 308 | 309 | # append the maximum extension(Kb) to dataframe 310 | max_ext_length = max_ext // 2 * resolution / 1000 311 | 312 | else: 313 | max_ext_length = np.nan 314 | 315 | max_ext_list.append(max_ext_length) 316 | 317 | regions['perc_res_list'] = perc_res_list 318 | regions['max_extension'] = max_ext_list 319 | 320 | return regions 321 | 322 | 323 | def background_evaluation( 324 | clr, background_clr, feature, extension_length, 325 | half_width, offset, norm = 'VC_SQRT' 326 | ): 327 | """ 328 | Compare interactions between Repli-HiC and BL-HiC and 329 | evaluate the quality of summits. We only leave summits with 330 | positive value after matrix subtraction. 331 | 332 | Mention: your dataframe has been sorted by chromosome names. 333 | """ 334 | feature = feature.copy() 335 | columns = ['chrom', 'start', 'end', 'name', 'SoN', 'strand'] 336 | 337 | if not feature.columns.isin(columns).any(): 338 | feature.columns = columns 339 | 340 | feature = feature.sort_values(by = 'chrom').reset_index(drop = True) 341 | # get resolution 342 | assert clr.binsize == background_clr.binsize, 'Unmatched resolution' 343 | resolution = clr.binsize 344 | half_width = half_width // resolution 345 | 346 | # remove 'chr' label 347 | if all(['chr' not in i for i in clr.chromnames]): 348 | if feature.chrom.str.contains('chr').all(): 349 | feature.loc[:, 'chrom'] = [i[3:] for i in feature.chrom] 350 | 351 | chrom_list = [] 352 | val_list = [] 353 | pos_ratio_list = [] 354 | neg_ratio_list = [] 355 | for index, row in feature.iterrows(): 356 | chrom = row['chrom'] 357 | init_bin = (row['end'] + row['start']) // resolution // 2 358 | 359 | if not chrom in chrom_list: 360 | chrom_list.append(chrom) 361 | mat = clr.matrix(balance=norm).fetch(chrom) 362 | background_mat = background_clr.matrix(balance=norm).fetch(chrom) 363 | mat_subtraction = mat - background_mat 364 | 365 | try: 366 | extension_length = row['max_extension'] * 1000 367 | except Exception as e: 368 | extension_length = extension_length 369 | 370 | target_plumb_val = np.asarray( 371 | [i for i in plumb_sum( 372 | mat = mat_subtraction, 373 | half_width = half_width, 374 | init_bin = init_bin, extension_length = extension_length, 375 | resolution = resolution, offset = offset 376 | )] 377 | ) 378 | 379 | positive_value = target_plumb_val[target_plumb_val>0] 380 | positive_value_ratio = len(positive_value) / len(target_plumb_val) 381 | 382 | negative_value = target_plumb_val[target_plumb_val<=0] 383 | negative_value_ratio = len(negative_value) / len(target_plumb_val) 384 | 385 | 386 | if len(positive_value) > len(negative_value): 387 | val_list.append(True) 388 | else: 389 | val_list.append(False) 390 | 391 | pos_ratio_list.append(positive_value_ratio) 392 | neg_ratio_list.append(negative_value_ratio) 393 | 394 | feature.loc[:, 'pos_ratio'] = pos_ratio_list 395 | feature.loc[:, 'neg_ratio'] = neg_ratio_list 396 | feature.loc[:, 'subtraction_value'] = val_list 397 | 398 | return feature 399 | 400 | -------------------------------------------------------------------------------- /lib/generate_summits.py: -------------------------------------------------------------------------------- 1 | def generate_summits_bed(clr, track, out_dir): 2 | 3 | resolution = clr.binsize 4 | suffix = '_' + str(resolution // 1000) + 'kb.bed' 5 | 6 | out_dir = out_dir + 'SoN_summits/' 7 | os.system('mkdir %s' % out_dir) 8 | 9 | for chrom in clr.chromnames: 10 | chrom = 'chr' + chrom 11 | 12 | # get SoN signal tracks for targeted chromosome 13 | signal_filter = track[track[0] == chrom] 14 | signal_filter_value = signal_filter[3].values 15 | 16 | # When find summits, we ignore the negative SoN values 17 | signal_filter_value[signal_filter_value < 0] = 0 18 | signal_filter[3] = signal_filter_value 19 | 20 | # get positions of summits 21 | poss, proms = find_peak_prominence(signal_filter[3].values) 22 | 23 | chr_cord_start = [i * resolution for i in poss] 24 | chr_cord_end = [(i + 1) * resolution for i in poss] 25 | names = np.repeat('.', len(poss)) 26 | strands = np.repeat('.', len(poss)) 27 | 28 | # get SoN score 29 | SoN_values = signal_filter[3].values[poss] 30 | 31 | data_dict = { 32 | 'chr': np.repeat(chrom, len(poss)), 33 | 'start': chr_cord_start, 34 | 'end': chr_cord_end, 35 | 'name': names, 36 | 'score': SoN_values, 37 | 'strand': strands 38 | } 39 | 40 | output = chrom + suffix 41 | df = pd.DataFrame(data_dict) 42 | df.to_csv( 43 | out_dir + output, 44 | sep='\t', 45 | header=None, 46 | index=None 47 | ) 48 | 49 | # merge all summits into one file 50 | os.system( 51 | 'cat %s*.bed > %sSummits_%s_merged.bed' % (out_dir, out_dir, resolution) 52 | ) 53 | 54 | # remove summits for individual chromosome 55 | os.system( 56 | 'rm %schr*' % out_dir 57 | ) 58 | -------------------------------------------------------------------------------- /lib/ks_test.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | from lib.fountain_extension import * 3 | 4 | def ks_test(mat, half_width, mid, extension_length, coverage_ratio, resolution, offset): 5 | 6 | up_bkg_per_dist = set_background( 7 | mat=mat, half_width=half_width, extension_length=extension_length, resolution=resolution, 8 | offset=offset, bin_idx=mid, orientation='upstream', coverage_ratio=coverage_ratio 9 | ) 10 | 11 | down_bkg_per_dist = set_background( 12 | mat=mat, half_width=half_width, extension_length=extension_length, resolution = resolution, 13 | offset=offset, bin_idx=mid, orientation='downstream', coverage_ratio=coverage_ratio 14 | ) 15 | 16 | tkg_plumb_per_dist = center_area_plumb_sum( 17 | mat=mat, half_width=half_width, extension_length=extension_length, resolution=resolution, 18 | offset=offset, bin_idx=mid, coverage_ratio=coverage_ratio 19 | ) 20 | 21 | if np.all( 22 | [isinstance(i, np.ndarray) for i in [up_bkg_per_dist, down_bkg_per_dist, tkg_plumb_per_dist]] 23 | ): 24 | bkg_ave = np.nanmean([up_bkg_per_dist, down_bkg_per_dist], axis=0) 25 | kstest_res = ks_2samp(tkg_plumb_per_dist, bkg_ave) 26 | 27 | return kstest_res 28 | 29 | else: 30 | return np.nan 31 | 32 | # make offset = 0 33 | def make_ks_test(clr, regions, half_width, norm, coverage_ratio, offset, use_control=True): 34 | ''' 35 | for each of candidate fountain, we use Kolmogorov–Smirnov test to verify its credibility 36 | 37 | Parameters 38 | ---------- 39 | mat: ndarray object 40 | 41 | 42 | Returns 43 | ------- 44 | regions: DataFrame object 45 | regions of candidates containing p-value and FDR 46 | 47 | ''' 48 | regions = regions.copy() 49 | resolution = clr.binsize 50 | 51 | if not 'max_extension' in regions.columns: 52 | raise TypeError( 53 | 'Invalid dataframe, you have to calculate the length of extension' 54 | ) 55 | 56 | chrom_list = [] 57 | ks_res_list = [] 58 | for index, row in regions.iterrows(): 59 | chrom = row['chrom'][3:] 60 | mid = (row['end'] + row['start']) // resolution // 2 61 | extension_length = row['max_extension'] * 1000 62 | 63 | if np.isnan(extension_length) or offset >= extension_length: 64 | ks_res = np.nan 65 | 66 | else: 67 | if chrom in chrom_list: 68 | 69 | ks_res = ks_test( 70 | mat=mat, half_width=half_width, mid=mid, extension_length=extension_length, 71 | coverage_ratio=coverage_ratio, resolution=resolution, offset=offset 72 | ) 73 | 74 | else: 75 | chrom_list.append(chrom) 76 | mat = clr.matrix(balance = norm).fetch(chrom) 77 | 78 | ks_res = ks_test( 79 | mat=mat, half_width=half_width, mid=mid, extension_length=extension_length, 80 | coverage_ratio=coverage_ratio, resolution=resolution, offset=offset 81 | ) 82 | 83 | ks_res_list.append(ks_res) 84 | 85 | regions['p_value'] = [ 86 | i.pvalue if isinstance( 87 | i, scipy.stats._stats_py.KstestResult 88 | ) else np.nan for i in ks_res_list 89 | ] 90 | 91 | return regions 92 | -------------------------------------------------------------------------------- /lib/merge_fountains.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | 3 | def merge_fountains(regions, max_distance = 50000): 4 | 5 | regions = regions.copy() 6 | 7 | # chrom list 8 | chroms = regions['chrom'].unique() 9 | # list of dataframe index for storing the best fountain candidates 10 | unique_index_list = [] 11 | 12 | for chrom in chroms: 13 | df = regions[regions['chrom'] == chrom] 14 | df_starts = np.asarray(df['start'], dtype = int) 15 | 16 | upstream_bound = df_starts - max_distance 17 | downstream_bound = df_starts + max_distance 18 | 19 | for up, down in zip(upstream_bound, downstream_bound): 20 | df_overlap = df[ 21 | (df['start'] >= up) & (df['start'] <= down) 22 | ] 23 | 24 | # record the dataframe index for the best fountain candidate 25 | if len(df_overlap) > 1: 26 | df_overlap_score = df_overlap['signal_noise_average_background'].values 27 | df_overlap_row_index = list(df_overlap.index) 28 | 29 | max_idx = np.argmax(df_overlap_score) 30 | df_max_idx = df_overlap.iloc[max_idx].name 31 | 32 | # if the max index has been stored in the list 33 | if not df_max_idx in unique_index_list: 34 | 35 | try: 36 | if unique_index_list[-1] in df_overlap_row_index: 37 | unique_index_list.pop() 38 | except IndexError: 39 | unique_index_list.append(df_overlap.index[0]) 40 | 41 | unique_index_list.append(df_max_idx) 42 | 43 | else: 44 | # if this fountain is unique in this region, 45 | # just record the index of this line 46 | unique_index_list.append(df_overlap.index[0]) 47 | 48 | return regions.iloc[unique_index_list] -------------------------------------------------------------------------------- /lib/quality_filter.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | 3 | def filter_extension(region_file, threshold=0.6): 4 | ext_list = region_file['perc_res_list'] 5 | 6 | func = lambda x: len(x[x > threshold]) >= 1 7 | 8 | bool_list = [func(np.asarray(i)) for i in ext_list] 9 | 10 | return bool_list -------------------------------------------------------------------------------- /lib/rotation.py: -------------------------------------------------------------------------------- 1 | import cooler 2 | import numpy as np 3 | import pandas as pd 4 | import pylab 5 | import math 6 | 7 | 8 | def _transform(theta): 9 | 10 | import numpy as np 11 | return theta * np.pi / 180 12 | 13 | def cos(theta): 14 | return np.cos(_transform(theta)) 15 | 16 | def sin(theta): 17 | return np.sin(_transform(theta)) 18 | 19 | def rotate( 20 | mat, theta, center, x_cord, y_cord, 21 | fill_mat = False, fill_value = 10 22 | ): 23 | ''' 24 | :param theta: theta > 0, counter-clockwise, else clockwise 25 | ''' 26 | 27 | # judge the orientation of rotation 28 | if theta >= 0: 29 | rotation_mat = np.array([[cos(theta), -sin(theta)], 30 | [sin(theta), cos(theta)]]) 31 | else: 32 | theta = abs(theta) 33 | rotation_mat = np.array([[cos(theta), sin(theta)], 34 | [-sin(theta), cos(theta)]]) 35 | 36 | # Let's rotate the cord! 37 | cord_list = [] 38 | for i, j in zip(x_cord, y_cord): 39 | x, y = i - center[0], j - center[1] 40 | tmp_cord = np.dot(rotation_mat, (x, y)) 41 | tmp_cord[0] = tmp_cord[0] + center[0] 42 | tmp_cord[1] = tmp_cord[1] + center[1] 43 | cord_list.append(tmp_cord) 44 | 45 | # Extract the values 46 | value_list = [] 47 | for i in cord_list: 48 | value_list.append(mat[int(i[0]), int(i[1])]) 49 | value_list = np.asarray(value_list) 50 | value_list[np.isinf(value_list)] = np.nan 51 | 52 | # Fill the matrix 53 | if fill_mat: 54 | for i in cord_list: 55 | mat[int(i[0]), int(i[1])] = fill_value 56 | return mat 57 | 58 | return value_list 59 | 60 | 61 | 62 | -------------------------------------------------------------------------------- /lib/signal_over_noise.py: -------------------------------------------------------------------------------- 1 | from multiprocessing import Pool 2 | from scipy.stats import ks_2samp 3 | from .diagonal_plumb import * 4 | import pandas as pd 5 | import numpy as np 6 | import cooler 7 | import sys 8 | import os 9 | import scipy 10 | 11 | 12 | def ks_test(mat, half_width, mid, extension_length, offset, coverage_ratio, resolution): 13 | 14 | up_bkg_per_dist = set_background( 15 | mat=mat, half_width=half_width, extension_length=extension_length, resolution=resolution, 16 | offset=offset, bin_idx=mid, orientation='upstream', coverage_ratio=coverage_ratio 17 | ) 18 | 19 | down_bkg_per_dist = set_background( 20 | mat=mat, half_width=half_width, extension_length=extension_length, resolution = resolution, 21 | offset=offset, bin_idx=mid, orientation='downstream', coverage_ratio=coverage_ratio 22 | ) 23 | 24 | tkg_plumb_per_dist = center_area_plumb_sum( 25 | mat=mat, half_width=half_width, extension_length=extension_length, resolution=resolution, 26 | offset=offset, bin_idx=mid, coverage_ratio=coverage_ratio 27 | ) 28 | 29 | if np.all( 30 | [isinstance(i, np.ndarray) for i in [up_bkg_per_dist, down_bkg_per_dist, tkg_plumb_per_dist]] 31 | ): 32 | bkg_ave = np.nanmean([up_bkg_per_dist, down_bkg_per_dist], axis=0) 33 | kstest_res = ks_2samp(tkg_plumb_per_dist, bkg_ave) 34 | 35 | return kstest_res 36 | 37 | else: 38 | return np.nan 39 | 40 | 41 | def calculate_coverage(plumb_signal): 42 | ''' 43 | Calculate coverage ratio when perform plumb 44 | 45 | ''' 46 | 47 | plumb_signal[np.isnan(plumb_signal)] = 0 48 | 49 | # count ratio of non-zero element 50 | cov_ratio = np.count_nonzero(plumb_signal) / len(plumb_signal) 51 | 52 | return cov_ratio 53 | 54 | 55 | def set_background( 56 | mat, half_width, extension_length, bin_idx, offset, resolution, 57 | orientation = None, coverage_ratio = None 58 | ): 59 | ''' 60 | Used to calculate the background of plumbs, which will help 61 | to calculate the fountainess future 62 | 63 | Notes: 64 | The function is directly based on the plumb-pileup function 65 | 66 | ''' 67 | if coverage_ratio is None: 68 | raise ValueError('Empty coverage ratio.') 69 | 70 | # Upstream background 71 | if orientation == 'upstream': 72 | diag_plumb_val = np.asarray( 73 | [i for i in plumb_sum( 74 | mat = mat, half_width = half_width, 75 | init_bin = bin_idx - 2*half_width-1, 76 | extension_length = extension_length, 77 | offset = offset, resolution = resolution 78 | )] 79 | ) 80 | 81 | if len(diag_plumb_val) >= 1: 82 | cov_ratio = calculate_coverage(diag_plumb_val) 83 | 84 | else: 85 | cov_ratio = 0 86 | 87 | if cov_ratio <= coverage_ratio: 88 | diag_plumb_val = np.nan 89 | 90 | 91 | elif orientation == 'downstream': 92 | diag_plumb_val = np.asarray( 93 | [i for i in plumb_sum( 94 | mat = mat, half_width = half_width, 95 | init_bin = bin_idx + 2*half_width+1, 96 | extension_length = extension_length, 97 | offset = offset, resolution = resolution 98 | )] 99 | ) 100 | if len(diag_plumb_val) >= 1: 101 | cov_ratio = calculate_coverage(diag_plumb_val) 102 | 103 | else: 104 | cov_ratio = 0 105 | 106 | if cov_ratio <= coverage_ratio: 107 | diag_plumb_val = np.nan 108 | 109 | elif orientation is None: 110 | raise TypeError('Please input orientation of background') 111 | 112 | else: 113 | raise TypeError('Invalid orientation') 114 | 115 | return diag_plumb_val 116 | 117 | 118 | def center_area_plumb_sum( 119 | mat, half_width, extension_length, 120 | bin_idx, offset, resolution, coverage_ratio = None 121 | ): 122 | 123 | if coverage_ratio is None: 124 | raise ValueError('Empty coverage ratio.') 125 | 126 | target_plumb_val = np.asarray( 127 | [i for i in plumb_sum( 128 | mat = mat, 129 | half_width = half_width, 130 | init_bin = bin_idx, extension_length = extension_length, 131 | resolution = resolution, offset = offset 132 | )] 133 | ) 134 | 135 | if len(target_plumb_val) >= 1: 136 | cov_ratio = calculate_coverage(target_plumb_val) 137 | 138 | else: 139 | cov_ratio = 0 140 | 141 | if cov_ratio <= coverage_ratio: 142 | target_plumb_val = np.nan 143 | 144 | 145 | return target_plumb_val 146 | 147 | 148 | def calculate_signal_noise_ratio_score( 149 | mat, half_width, extension_length, 150 | resolution, offset, coverage_ratio = 0.2, 151 | use_mean = True 152 | ): 153 | ''' 154 | calculate a statistics to measure the strength of fountain 155 | 156 | Parameters 157 | ---------- 158 | mat: ndarray object 159 | hic matrix 160 | 161 | half_width: int object 162 | number of bins of padding regions for its center 163 | 164 | extension_length: int object 165 | Length of extension (bp) 166 | 167 | Returns 168 | ------- 169 | fountain score: float object 170 | a kind of statistics to measure the strength of fountain 171 | 172 | ''' 173 | 174 | for idx in range(mat.shape[0]): 175 | up_bkg = set_background( 176 | mat=mat, half_width=half_width, extension_length=extension_length, 177 | offset=offset, bin_idx=idx, orientation = 'upstream', 178 | coverage_ratio=coverage_ratio, resolution=resolution 179 | ) 180 | 181 | down_bkg = set_background( 182 | mat=mat, half_width=half_width, extension_length=extension_length, 183 | offset=offset, bin_idx=idx, orientation = 'downstream', 184 | coverage_ratio=coverage_ratio, resolution=resolution 185 | ) 186 | 187 | tkg_plumb = center_area_plumb_sum( 188 | mat=mat, half_width=half_width, extension_length=extension_length, 189 | offset=offset, bin_idx=idx, coverage_ratio=coverage_ratio, resolution=resolution 190 | ) 191 | 192 | if np.all( 193 | [isinstance(i, np.ndarray) for i in [up_bkg, down_bkg, tkg_plumb]] 194 | ): 195 | # gradient for upstream / downstream 196 | bkg_ave = np.nanmean( 197 | [np.nansum(up_bkg), np.nansum(down_bkg)] 198 | ) 199 | 200 | bkg_gradient = np.nansum(tkg_plumb) / bkg_ave 201 | 202 | # set np.nan/inf to 0 203 | if np.isnan(bkg_gradient) or np.isinf(bkg_gradient): 204 | bkg_gradient = 1 205 | 206 | if use_mean: 207 | fountain_score = np.nanmean(tkg_plumb) * np.log(bkg_gradient) 208 | else: 209 | fountain_score = np.nanmedian(tkg_plumb) * np.log(bkg_gradient) 210 | 211 | else: 212 | fountain_score = np.nan 213 | 214 | yield fountain_score 215 | 216 | 217 | def worker(args): 218 | mat, half_width, extension_length, resolution, offset, coverage_ratio, idx = args 219 | tkg_plumb = center_area_plumb_sum( 220 | mat, half_width, extension_length, idx, offset, resolution, coverage_ratio 221 | ) 222 | 223 | print(f"This is bin {idx}") 224 | 225 | if isinstance(tkg_plumb, np.ndarray): 226 | return np.nansum(tkg_plumb) 227 | else: 228 | return np.nan 229 | 230 | def calculate_strength_parallel(mat, half_width, extension_length, resolution, offset, coverage_ratio, CPU): 231 | 232 | print('Calculating parallel......') 233 | print(f'------Your input CPU is {CPU}------') 234 | 235 | with Pool(CPU) as pool: 236 | args_list = [(mat, half_width, extension_length, resolution, offset, coverage_ratio, idx) for idx in range(mat.shape[0])] 237 | results = pool.map(worker, args_list) 238 | return results 239 | 240 | 241 | def calculate_strength_single(mat, half_width, extension_length, resolution, offset, coverage_ratio): 242 | 243 | for idx in range(mat.shape[0]): 244 | 245 | tkg_plumb = center_area_plumb_sum( 246 | mat, half_width, extension_length, idx, offset, resolution, coverage_ratio 247 | ) 248 | 249 | if isinstance(tkg_plumb, np.ndarray): 250 | yield np.nansum(tkg_plumb) 251 | else: 252 | yield np.nan 253 | 254 | 255 | 256 | def read_chrom_sizes(chrominfo_file, prefix=""): 257 | with open(chrominfo_file, 'r') as f: 258 | chrom_sizes = {} 259 | for line in f: 260 | chrom, size = line.strip().split() 261 | chrom_id = f"{prefix}{chrom.replace('chr', '')}" 262 | chrom_sizes[chrom_id] = int(size) 263 | return chrom_sizes 264 | 265 | 266 | -------------------------------------------------------------------------------- /lib/trans_to_bedpe.py: -------------------------------------------------------------------------------- 1 | import pandas as pd 2 | 3 | def dataframe_to_bedpe(regions, resolution): 4 | 5 | up_coords_s, down_coords_s = [], [] 6 | up_coords_e, down_coords_e = [], [] 7 | chrom_list = [] 8 | for index, row in regions.iterrows(): 9 | chrom = row['chrom'] 10 | 11 | mid_coord_s = int(row['start'] + row['end']) // 2 12 | 13 | up_coord_s = int(mid_coord_s - row['max_extension'] * 1000) 14 | up_coord_e = int(up_coord_s + resolution) 15 | 16 | down_coord_s = int(mid_coord_s + row['max_extension'] * 1000) 17 | down_coord_e = int(down_coord_s + resolution) 18 | 19 | chrom_list.append(chrom) 20 | 21 | up_coords_s.append(up_coord_s) 22 | up_coords_e.append(up_coord_e) 23 | 24 | down_coords_s.append(down_coord_s) 25 | down_coords_e.append(down_coord_e) 26 | 27 | df = pd.DataFrame( 28 | {'chr1': chrom_list, 29 | 'x1': up_coords_s, 30 | 'x2': up_coords_e, 31 | 'chr2': chrom_list, 32 | 'y1': down_coords_s, 33 | 'y2': down_coords_e} 34 | ) 35 | 36 | return df 37 | 38 | 39 | def label_sampling_box(regions, resolution, half_width): 40 | 41 | center_upstream_bound_list, center_downstream_bound_list = [], [] 42 | upstream_upper_bound_list, downstream_lower_bound_list = [], [] 43 | chrom_list = [] 44 | for index, row in regions.iterrows(): 45 | 46 | center = row['start'] 47 | chrom = row['chrom'] 48 | 49 | center_upstream_bound = center - half_width * resolution 50 | center_downstream_bound = center + half_width * resolution 51 | 52 | upstream_upper_bound = center_upstream_bound - 2 * half_width * resolution 53 | downstream_lower_bound = center_downstream_bound + 2 * half_width * resolution 54 | 55 | center_upstream_bound_list.append(center_upstream_bound) 56 | center_downstream_bound_list.append(center_downstream_bound) 57 | upstream_upper_bound_list.append(upstream_upper_bound) 58 | downstream_lower_bound_list.append(downstream_lower_bound) 59 | chrom_list.append(chrom) 60 | 61 | center_upstream_bound_list = np.asarray(center_upstream_bound_list) 62 | center_downstream_bound_list = np.asarray(center_downstream_bound_list) 63 | upstream_upper_bound_list = np.asarray(upstream_upper_bound_list) 64 | downstream_lower_bound_list = np.asarray(downstream_lower_bound_list) 65 | 66 | df_upstream_upper_bound_list = pd.DataFrame( 67 | {'chr1': chrom_list, 68 | 'x1': upstream_upper_bound_list, 69 | 'x2': upstream_upper_bound_list + resolution, 70 | 'chr2': chrom_list, 71 | 'y1': upstream_upper_bound_list, 72 | 'y2': upstream_upper_bound_list + resolution} 73 | ) 74 | 75 | df_downstream_lower_bound_list = pd.DataFrame( 76 | {'chr1': chrom_list, 77 | 'x1': downstream_lower_bound_list, 78 | 'x2': downstream_lower_bound_list + resolution, 79 | 'chr2': chrom_list, 80 | 'y1': downstream_lower_bound_list, 81 | 'y2': downstream_lower_bound_list + resolution} 82 | ) 83 | 84 | df_center_upstream_bound_list = pd.DataFrame( 85 | {'chr1': chrom_list, 86 | 'x1': center_upstream_bound_list, 87 | 'x2': center_upstream_bound_list + resolution, 88 | 'chr2': chrom_list, 89 | 'y1': center_upstream_bound_list, 90 | 'y2': center_upstream_bound_list + resolution} 91 | ) 92 | 93 | df_center_downstream_bound_list = pd.DataFrame( 94 | {'chr1': chrom_list, 95 | 'x1': center_downstream_bound_list, 96 | 'x2': center_downstream_bound_list + resolution, 97 | 'chr2': chrom_list, 98 | 'y1': center_downstream_bound_list, 99 | 'y2': center_downstream_bound_list + resolution} 100 | ) 101 | 102 | df_merged = pd.concat( 103 | [df_upstream_upper_bound_list, df_downstream_lower_bound_list, 104 | df_center_upstream_bound_list, df_center_downstream_bound_list] 105 | ) 106 | 107 | return df_merged 108 | -------------------------------------------------------------------------------- /lib/util.py: -------------------------------------------------------------------------------- 1 | import subprocess 2 | import bioframe 3 | import pandas as pd 4 | 5 | def align_track_with_chromsize(track, chromsizes): 6 | """ 7 | Aligns a signal track with chromosome sizes, ensuring that 'end' coordinates do not exceed chromosome sizes. 8 | 9 | Args: 10 | track (DataFrame): Signal track of SoN. 11 | chromsizes (DataFrame): DataFrame containing information of chromosome sizes. 12 | 13 | Returns: 14 | DataFrame: Refined SoN with adjusted 'end' coordinates. 15 | """ 16 | track = track.copy() 17 | 18 | # Get chromosome information from the track 19 | chrom = track['chr'].unique().item() 20 | 21 | # Get chromosome size 22 | size = chromsizes.at[chrom] 23 | 24 | # Update 'end' coordinates exceeding chromosome size 25 | track.loc[track['end'] > size, 'end'] = size 26 | 27 | return track 28 | 29 | 30 | def bedgraph_to_bigwig(bedGraphToBigWig, track_path, chromsizes_path, bigwig_output_path): 31 | """ 32 | 33 | Args: 34 | bedGraphToBigWig (str): Path to bedGraphToBigWig from UCSC 35 | bedgraph_path (str): Path to the input bedGraph file. 36 | chromsize_path (str): Path to the chromosome size file. 37 | bigwig_output_path (str): Path to save the output BigWig file. 38 | 39 | Returns: 40 | None 41 | """ 42 | cmd = [bedGraphToBigWig, track_path, chromsizes_path, bigwig_output_path] 43 | subprocess.run(cmd) --------------------------------------------------------------------------------