├── .gitignore ├── LICENSE ├── README.md ├── bin ├── CPC2.py ├── CPC2_output_peptide.py ├── compress.py └── seqio.py ├── data ├── cpc2.model ├── cpc2.range └── example.fa └── libs └── libsvm └── libsvm-3.18.tar.gz /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | env/ 12 | build/ 13 | develop-eggs/ 14 | dist/ 15 | downloads/ 16 | eggs/ 17 | .eggs/ 18 | lib/ 19 | lib64/ 20 | parts/ 21 | sdist/ 22 | var/ 23 | wheels/ 24 | *.egg-info/ 25 | .installed.cfg 26 | *.egg 27 | 28 | # PyInstaller 29 | # Usually these files are written by a python script from a template 30 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 31 | *.manifest 32 | *.spec 33 | 34 | # Installer logs 35 | pip-log.txt 36 | pip-delete-this-directory.txt 37 | 38 | # Unit test / coverage reports 39 | htmlcov/ 40 | .tox/ 41 | .coverage 42 | .coverage.* 43 | .cache 44 | nosetests.xml 45 | coverage.xml 46 | *.cover 47 | .hypothesis/ 48 | 49 | # Translations 50 | *.mo 51 | *.pot 52 | 53 | # Django stuff: 54 | *.log 55 | local_settings.py 56 | 57 | # Flask stuff: 58 | instance/ 59 | .webassets-cache 60 | 61 | # Scrapy stuff: 62 | .scrapy 63 | 64 | # Sphinx documentation 65 | docs/_build/ 66 | 67 | # PyBuilder 68 | target/ 69 | 70 | # Jupyter Notebook 71 | .ipynb_checkpoints 72 | 73 | # pyenv 74 | .python-version 75 | 76 | # celery beat schedule file 77 | celerybeat-schedule 78 | 79 | # SageMath parsed files 80 | *.sage.py 81 | 82 | # dotenv 83 | .env 84 | 85 | # virtualenv 86 | .venv 87 | venv/ 88 | ENV/ 89 | 90 | # Spyder project settings 91 | .spyderproject 92 | .spyproject 93 | 94 | # Rope project settings 95 | .ropeproject 96 | 97 | # mkdocs documentation 98 | /site 99 | 100 | # mypy 101 | .mypy_cache/ 102 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU General Public License is a free, copyleft license for 11 | software and other kinds of works. 12 | 13 | The licenses for most software and other practical works are designed 14 | to take away your freedom to share and change the works. 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It is safest 630 | to attach them to the start of each source file to most effectively 631 | state the exclusion of warranty; and each file should have at least 632 | the "copyright" line and a pointer to where the full notice is found. 633 | 634 | 635 | Copyright (C) 636 | 637 | This program is free software: you can redistribute it and/or modify 638 | it under the terms of the GNU General Public License as published by 639 | the Free Software Foundation, either version 3 of the License, or 640 | (at your option) any later version. 641 | 642 | This program is distributed in the hope that it will be useful, 643 | but WITHOUT ANY WARRANTY; without even the implied warranty of 644 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 645 | GNU General Public License for more details. 646 | 647 | You should have received a copy of the GNU General Public License 648 | along with this program. If not, see . 649 | 650 | Also add information on how to contact you by electronic and paper mail. 651 | 652 | If the program does terminal interaction, make it output a short 653 | notice like this when it starts in an interactive mode: 654 | 655 | Copyright (C) 656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 657 | This is free software, and you are welcome to redistribute it 658 | under certain conditions; type `show c' for details. 659 | 660 | The hypothetical commands `show w' and `show c' should show the appropriate 661 | parts of the General Public License. Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . 675 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | CPC2 standalone 2 | ==== 3 | 4 | * 2020-01-13 14:58, Yu-jian Kang 5 | * This is a python 2 verison of CPC2 (same with the version of the original paper). 6 | * Thanks for helps from **HyperOdin**, there is a python 3 version (the release of *CPC2_standalone_python3 v1.0.1*) 7 | 8 | 1 Pre-requisite: 9 | ---- 10 | a. Biopython package: a local version could be downloaded from 11 | http://biopython.org/wiki/Download 12 | 13 | 2 Install 14 | ---- 15 | a. Unpack the tarball: 16 | 17 | tom@linux$ gzip -dc CPC2-beta.tar.gz | tar xf - 18 | 19 | b. Build third-part packages: 20 | 21 | tom@linux$ cd CPC2-beta 22 | tom@linux$ export CPC_HOME="$PWD" 23 | tom@linux$ cd libs/libsvm 24 | tom@linux$ gzip -dc libsvm-3.18.tar.gz | tar xf - 25 | tom@linux$ cd libsvm-3.18 26 | tom@linux$ make clean && make 27 | 28 | 3 Run the predict 29 | ---- 30 | tom@linux$ cd $CPC_HOME 31 | tom@linux$ bin/CPC2.py -i (input_seq) -o (result_in_table) 32 | 33 | Example: 34 | 35 | tom@linux$ bin/CPC2.py -i data/example.fa -o example_output 36 | 37 | If you want to output predicted peptide sequence, use CPC2_output_peptide.py with "--ORF" option: 38 | 39 | tom@linux$ bin/CPC2_output_peptide.py -i data/example.fa -o example_output --ORF 40 | 41 | 4 Output result 42 | ---- 43 | Result in table format (delimited by tab):
44 | #ID peptide_length Fickett_score isoelectric_point ORF_integrity coding_probability coding_label 45 | 46 | Contact 47 | ---- 48 | >See the website for tutorial and more details. (http://cpc2.cbi.pku.edu.cn)
49 | 50 | >This is a beta version of CPC2, if have any questions please report to us.
51 | 52 | >Contact: cpc@mail.cbi.pku.edu.cn 53 | -------------------------------------------------------------------------------- /bin/CPC2.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python 2 | 3 | # This version is edited at 20190124 for compatibility on OS system 4 | 5 | import sys 6 | import os 7 | import re 8 | import commands 9 | import time 10 | from optparse import OptionParser,OptionGroup 11 | 12 | import numpy as np 13 | from Bio.Seq import Seq 14 | from Bio.SeqUtils import ProtParam 15 | 16 | import seqio 17 | 18 | def __main(): 19 | start_time = time.time() 20 | usage = "usage: %prog [options] -i input.fasta -o output_file" 21 | description = "Contact: Kang Yujian " 22 | parser = OptionParser(usage,version="%prog 0.1",description = description) 23 | Common_group = OptionGroup(parser,"Common Options") 24 | Common_group.add_option("-i",dest="fasta",help="input sequence in fasta format [Required]",metavar="FILE",type="string",default=None) 25 | Common_group.add_option("-o",dest="outfile",help="output file [Default: cpc2output.txt]",metavar="FILE",type="string",default="cpc2output.txt") 26 | Common_group.add_option("-r",dest="reverse",help="also check the reverse strand [Default: FALSE]",action="store_true") 27 | Common_group.add_option("--ORF",dest="ORF",help="output the start position of longest ORF [Default: FALSE]",action="store_true") 28 | parser.add_option_group(Common_group) 29 | (options, args) = parser.parse_args() 30 | if options.fasta == None: 31 | parser.print_help() 32 | return -1 33 | else: 34 | if not os.path.isfile(options.fasta): 35 | sys.stderr.write("[ERROR] %s is not a file\n"%options.fasta) 36 | return -1 37 | if options.reverse: 38 | strand = "-" 39 | else: 40 | strand = "+" 41 | if options.ORF: 42 | output_orf = 1 43 | else: 44 | output_orf = 0 45 | if calculate_potential(options.fasta,strand,output_orf,options.outfile): 46 | return 1 47 | sys.stderr.write("[INFO] cost time: %ds\n"%(time.time()-start_time)) 48 | return 0 49 | 50 | class FindCDS: 51 | ''' 52 | Find the most like CDS in a given sequence 53 | The most like CDS is the longest ORF found in the sequence 54 | When having same length, the upstream ORF is printed 55 | modified from source code of CPAT 1.2.1 downloaded from https://sourceforge.net/projects/rna-cpat/files/?source=navbar 56 | ''' 57 | def __init__(self,seq): 58 | self.seq = seq 59 | self.result = (0,0,0,0,0) 60 | self.longest = 0 61 | self.basepair = {"A":"T","T":"A","U":"A","C":"G","G":"C","N":"N","X":"X"} 62 | 63 | def _reversecompliment(self): 64 | return "".join(self.basepair[base] for base in self.seq)[::-1] 65 | 66 | def get_codons(self,frame_number): 67 | ''' 68 | Record every nucleotide triplet and its coordinate position for input sequence in one frame 69 | ''' 70 | coordinate = frame_number 71 | while coordinate + 3 <= len(self.seq): 72 | yield (self.seq[coordinate:coordinate+3], coordinate) 73 | coordinate += 3 74 | 75 | def find_longest_in_one(self,myframe,direction,start_codon,stop_codon): 76 | ''' 77 | find the longest ORF in one reading myframe 78 | ''' 79 | triplet_got = self.get_codons(myframe) 80 | starts = start_codon 81 | stops = stop_codon 82 | ''' 83 | Extend sequence by triplet after start codon encountered 84 | End ORF extension when stop codon encountered 85 | ''' 86 | while True: 87 | try: 88 | codon,index = triplet_got.next() 89 | except StopIteration: 90 | break 91 | if codon in starts and codon not in stops: 92 | ''' 93 | find the ORF start 94 | ''' 95 | orf_start = index 96 | end_extension = False 97 | while True: 98 | try: 99 | codon,index = triplet_got.next() 100 | except StopIteration: 101 | end_extension = True 102 | integrity = -1 103 | if codon in stops: 104 | integrity = 1 105 | end_extension = True 106 | if end_extension: 107 | orf_end = index + 3 108 | Length = (orf_end - orf_start) 109 | if Length > self.longest: 110 | self.longest = Length 111 | self.result = [direction,orf_start,orf_end,Length,integrity] 112 | if Length == self.longest and orf_start < self.result[1]: 113 | ''' 114 | if ORFs have same length, return the one that if upstream 115 | ''' 116 | self.result = [direction,orf_start,orf_end,Length,integrity] 117 | break 118 | 119 | def longest_orf(self,direction,start_codon={"ATG":None}, stop_codon={"TAG":None,"TAA":None,"TGA":None}): 120 | return_orf = "" 121 | for frame in range(3): 122 | self.find_longest_in_one(frame,"+",start_codon,stop_codon) 123 | return_orf = self.seq[self.result[1]:self.result[2]][:] 124 | start_coordinate = self.result[1] 125 | strand_direction = "+" 126 | orf_integrity = self.result[4] 127 | ''' 128 | Also check reverse chain if -r is chosen 129 | ''' 130 | if direction == "-": 131 | self.seq = self._reversecompliment() 132 | for frame in range(3): 133 | self.find_longest_in_one(frame,"-",start_codon,stop_codon) 134 | if self.result[0] == "-": 135 | return_orf = self.seq[self.result[1]:self.result[2]][:] 136 | start_coordinate = self.result[1] 137 | strand_direction = "-" 138 | orf_integrity = self.result[4] 139 | return return_orf,start_coordinate,strand_direction,orf_integrity 140 | 141 | 142 | class Fickett: 143 | ''' 144 | calculate Fickett TESTCODE for full sequence 145 | NAR 10(17) 5303-531 146 | modified from source code of CPAT 1.2.1 downloaded from https://sourceforge.net/projects/rna-cpat/files/?source=navbar 147 | ''' 148 | def __init__(self): 149 | '''new compiled Fickett look-up table''' 150 | self.position_parameter = [1.9,1.8,1.7,1.6,1.5,1.4,1.3,1.2,1.1,0.0] 151 | self.content_parameter = [0.33,0.31,0.29,0.27,0.25,0.23,0.21,0.19,0.17,0] 152 | self.position_probability = { 153 | "A":[0.51,0.55,0.57,0.52,0.48,0.58,0.57,0.54,0.50,0.36], 154 | "C":[0.29,0.44,0.55,0.49,0.52,0.60,0.60,0.56,0.51,0.38], 155 | "G":[0.62,0.67,0.74,0.65,0.61,0.62,0.52,0.41,0.31,0.17], 156 | "T":[0.51,0.60,0.69,0.64,0.62,0.67,0.58,0.48,0.39,0.24], 157 | } 158 | self.position_weight = {"A":0.062,"C":0.093,"G":0.205,"T":0.154} 159 | self.content_probability = { 160 | "A":[0.40,0.55,0.58,0.58,0.52,0.48,0.45,0.45,0.38,0.19], 161 | "C":[0.50,0.63,0.59,0.50,0.46,0.45,0.47,0.56,0.59,0.33], 162 | "G":[0.21,0.40,0.47,0.50,0.52,0.56,0.57,0.52,0.44,0.23], 163 | "T":[0.30,0.49,0.56,0.53,0.48,0.48,0.52,0.57,0.60,0.51] 164 | } 165 | self.content_weight = {"A":0.084,"C":0.076,"G":0.081,"T":0.055} 166 | 167 | 168 | def look_up_position_probability(self,value, base): 169 | ''' 170 | look up positional probability by base and value 171 | ''' 172 | if float(value) < 0: 173 | return None 174 | for idx,val in enumerate (self.position_parameter): 175 | if (float(value) >= val): 176 | return float(self.position_probability[base][idx]) * float(self.position_weight[base]) 177 | 178 | def look_up_content_probability(self,value, base): 179 | ''' 180 | look up content probability by base and value 181 | ''' 182 | if float(value) < 0: 183 | return None 184 | for idx,val in enumerate (self.content_parameter): 185 | if (float(value) >= val): 186 | return float(self.content_probability[base][idx]) * float(self.content_weight[base]) 187 | 188 | def fickett_value(self,dna): 189 | ''' 190 | calculate Fickett value from full RNA transcript sequence 191 | ''' 192 | if len(dna) < 2: 193 | return 0 194 | fickett_score=0 195 | dna=dna 196 | total_base = len(dna) 197 | A_content = float(dna.count("A"))/total_base 198 | C_content = float(dna.count("C"))/total_base 199 | G_content = float(dna.count("G"))/total_base 200 | T_content = float(dna.count("T"))/total_base 201 | 202 | phase_0 = dna[::3] 203 | phase_1 = dna[1::3] 204 | phase_2 = dna[2::3] 205 | 206 | phase_0_A = phase_0.count("A") 207 | phase_1_A = phase_1.count("A") 208 | phase_2_A = phase_2.count("A") 209 | phase_0_C = phase_0.count("C") 210 | phase_1_C = phase_1.count("C") 211 | phase_2_C = phase_2.count("C") 212 | phase_0_G = phase_0.count("G") 213 | phase_1_G = phase_1.count("G") 214 | phase_2_G = phase_2.count("G") 215 | phase_0_T = phase_0.count("T") 216 | phase_1_T = phase_1.count("T") 217 | phase_2_T = phase_2.count("T") 218 | 219 | A_content = float(phase_0_A + phase_1_A + phase_2_A)/total_base 220 | C_content = float(phase_0_C + phase_1_C + phase_2_C)/total_base 221 | G_content = float(phase_0_G + phase_1_G + phase_2_G)/total_base 222 | T_content = float(phase_0_T + phase_1_T + phase_2_T)/total_base 223 | A_position= np.max([phase_0_A,phase_1_A,phase_2_A])/(np.min([phase_0_A,phase_1_A,phase_2_A]) +1.0) 224 | C_position= np.max([phase_0_C,phase_1_C,phase_2_C])/(np.min([phase_0_C,phase_1_C,phase_2_C]) +1.0) 225 | G_position= np.max([phase_0_G,phase_1_G,phase_2_G])/(np.min([phase_0_G,phase_1_G,phase_2_G]) +1.0) 226 | T_position= np.max([phase_0_T,phase_1_T,phase_2_T])/(np.min([phase_0_T,phase_1_T,phase_2_T]) +1.0) 227 | 228 | fickett_score += self.look_up_content_probability(A_content,"A") 229 | fickett_score += self.look_up_content_probability(C_content,"C") 230 | fickett_score += self.look_up_content_probability(G_content,"G") 231 | fickett_score += self.look_up_content_probability(T_content,"T") 232 | 233 | fickett_score += self.look_up_position_probability(A_position,"A") 234 | fickett_score += self.look_up_position_probability(C_position,"C") 235 | fickett_score += self.look_up_position_probability(G_position,"G") 236 | fickett_score += self.look_up_position_probability(T_position,"T") 237 | 238 | return fickett_score 239 | 240 | #=================== 241 | 242 | def mRNA_translate(mRNA): 243 | return Seq(mRNA).translate() 244 | 245 | def protein_param(putative_seqprot): 246 | return putative_seqprot.isoelectric_point() 247 | 248 | def calculate_potential(fasta,strand,output_orf,outfile): 249 | ''' 250 | Calculate three features: putative peptide length,pI and Fickett 251 | And assess coding potential based on SVM model 252 | ''' 253 | strinfoAmbiguous = re.compile("X|B|Z|J|U",re.I) 254 | ptU = re.compile("U",re.I) 255 | ftmp_feat = file(outfile + ".feat","w") 256 | ftmp_svm = file(outfile + ".tmp.1","w") 257 | ftmp_result = file(outfile,"w") 258 | if output_orf == 1: 259 | my_header = ["#ID","transcript_length","peptide_length","Fickett_score","pI","ORF_integrity","ORF_Start","coding_probability","label"] 260 | else: 261 | my_header = ["#ID","transcript_length","peptide_length","Fickett_score","pI","ORF_integrity","coding_probability","label"] 262 | ftmp_result.write("\t".join(map(str,my_header))+"\n") 263 | fickett_obj = Fickett() 264 | for seq in seqio.fasta_read(fasta): 265 | seqid = seq.id 266 | seqRNA = ptU.sub("T",str(seq.seq).strip()) 267 | '''seqRNA:transcript full sequence''' 268 | seqRNA = seqRNA.upper() 269 | seqCDS,start_pos,orf_strand,orf_fullness = FindCDS(seqRNA).longest_orf(strand) 270 | '''seqCDS:longest ORF''' 271 | seqprot = mRNA_translate(seqCDS) 272 | pep_len = len(seqprot) #pep_len = len(seqprot.strip("*")) 273 | newseqprot = strinfoAmbiguous.sub("",str(seqprot)) 274 | '''exclude ambiguous amio acid X, B, Z, J, Y in peptide sequence''' 275 | fickett_score = fickett_obj.fickett_value(seqRNA) 276 | protparam_obj = ProtParam.ProteinAnalysis(str(newseqprot.strip("*"))) 277 | if pep_len > 0: 278 | #fickett_score = fickett_obj.fickett_value(seqCDS) 279 | start_pos = start_pos + 1 280 | isoelectric_point = protein_param(protparam_obj) 281 | else: 282 | #fickett_score = 0.0 283 | start_pos = 0 284 | orf_fullness = -1 285 | isoelectric_point = 0.0 286 | if output_orf == 1: 287 | output_line = [seqid,len(seqRNA),pep_len,fickett_score,isoelectric_point,orf_fullness,start_pos] 288 | else: 289 | output_line = [seqid,len(seqRNA),pep_len,fickett_score,isoelectric_point,orf_fullness] 290 | ftmp_result.write("\t".join(map(str,output_line))+"\n") 291 | ftmp_feat.write("\t".join(map(str,[seqid,len(seqRNA),pep_len,fickett_score,isoelectric_point,orf_fullness]))+"\n") 292 | ftmp_svm.write("".join(map(str,["999"," 1:",pep_len," 2:",fickett_score," 3:",isoelectric_point," 4:",orf_fullness]))+"\n") 293 | ftmp_result.close() 294 | ftmp_feat.close() 295 | ftmp_svm.close() 296 | #return 0 297 | 298 | ''' 299 | calculate the coding probability using LIBSVM 300 | ''' 301 | sys.stderr.write("[INFO] Predicting coding potential, please wait ...\n") 302 | 303 | ''' 304 | set directories and check depending tools existance 305 | ''' 306 | script_dir,filename = os.path.split(os.path.abspath(sys.argv[0])) 307 | data_dir = script_dir + "/../data/" 308 | lib_dir = script_dir + "/../libs/" 309 | app_svm_scale = lib_dir + "libsvm/libsvm-3.18/svm-scale" 310 | app_svm_predict = lib_dir + "libsvm/libsvm-3.18/svm-predict" 311 | os.system('test -x '+ app_svm_scale + ' || echo \"[ERROR] No excutable svm-scale on CPC2 path!\" > /dev/stderr') 312 | os.system('test -x '+ app_svm_predict + ' || echo \"[ERROR] No excutable svm-predict on CPC2 path!\" > /dev/stderr') 313 | 314 | cmd = app_svm_scale + ' -r ' + data_dir + 'cpc2.range ' + outfile + '.tmp.1 > ' + outfile + '.tmp.2 &&' 315 | cmd = cmd + app_svm_predict + ' -b 1 -q ' + outfile + '.tmp.2 ' + data_dir + 'cpc2.model ' + outfile + '.tmp.out' 316 | #cmd = cmd + 'awk -vOFS="\\t" \'{if ($1 == 1){print $2,"coding"} else if ($1 == 0){print $2,"noncoding"}}\' ' + outfile + '.tmp.1 > ' + outfile + '.tmp.2 &&' 317 | #cmd = cmd + 'paste ' + outfile + '.feat ' + outfile + '.tmp.2 >>' + outfile 318 | (exitstatus, outtext) = commands.getstatusoutput(cmd) 319 | 320 | '''deal with the output''' 321 | #print outfile + '.tmp.out' 322 | tmp_file = open(outfile + '.tmp.out','r') 323 | prob = {} 324 | i = 0 325 | # get libsvm output 326 | for line in tmp_file: 327 | i = i + 1 328 | array = line.split(' ') 329 | if array[0] == "1": 330 | label = "coding" 331 | else: 332 | label = "noncoding" 333 | prob[i] = str(array[1]) + '\t' + label 334 | tmp_file.close() 335 | # paste to features 336 | tmp_file = open(outfile,'r') 337 | out_file = open(outfile + '.txt','w') 338 | i = 0 339 | for line in tmp_file: 340 | i = i + 1 341 | if i == 1: 342 | out_file.write(line) 343 | else: 344 | line = line.rstrip('\n') 345 | out_file.write(line) 346 | out_file.write('\t' + prob[i] + '\n') 347 | tmp_file.close() 348 | out_file.close() 349 | # subprocess.call("Rscript " + outfile + '.r', shell=True) 350 | #except: 351 | # pass 352 | if exitstatus == 0: 353 | os.system('rm -f ' + outfile + '.tmp.1 ' + outfile + '.tmp.2 ' + outfile + '.tmp.out ' + outfile) 354 | rm_cmd = "rm -f " + outfile + '.feat' 355 | commands.getstatusoutput(rm_cmd) 356 | sys.stderr.write("[INFO] Running Done!\n") 357 | return 0 358 | else: 359 | sys.stderr.write("[ERROR] Prediction error!\n") 360 | return -1 361 | 362 | if __name__ == "__main__": 363 | sys.exit(__main()) 364 | -------------------------------------------------------------------------------- /bin/CPC2_output_peptide.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python 2 | 3 | # This version is edited at 20190124 for compatibility on OS system 4 | 5 | import sys 6 | import os 7 | import re 8 | import commands 9 | import time 10 | from optparse import OptionParser,OptionGroup 11 | 12 | import numpy as np 13 | from Bio.Seq import Seq 14 | from Bio.SeqUtils import ProtParam 15 | 16 | import seqio 17 | 18 | def __main(): 19 | start_time = time.time() 20 | usage = "usage: %prog [options] -i input.fasta -o output_file" 21 | description = "Contact: Kang Yujian " 22 | parser = OptionParser(usage,version="%prog 0.1",description = description) 23 | Common_group = OptionGroup(parser,"Common Options") 24 | Common_group.add_option("-i",dest="fasta",help="input sequence in fasta format [Required]",metavar="FILE",type="string",default=None) 25 | Common_group.add_option("-o",dest="outfile",help="output file [Default: cpc2output.txt]",metavar="FILE",type="string",default="cpc2output") 26 | Common_group.add_option("-r",dest="reverse",help="also check the reverse strand [Default: FALSE]",action="store_true") 27 | Common_group.add_option("--ORF",dest="ORF",help="output the putative peptide [Default: FALSE]",action="store_true") 28 | parser.add_option_group(Common_group) 29 | (options, args) = parser.parse_args() 30 | if options.fasta == None: 31 | parser.print_help() 32 | return -1 33 | else: 34 | if not os.path.isfile(options.fasta): 35 | sys.stderr.write("[ERROR] %s is not a file\n"%options.fasta) 36 | return -1 37 | if options.reverse: 38 | strand = "-" 39 | else: 40 | strand = "+" 41 | if options.ORF: 42 | output_orf = 1 43 | else: 44 | output_orf = 0 45 | if calculate_potential(options.fasta,strand,output_orf,options.outfile): 46 | return 1 47 | sys.stderr.write("[INFO] cost time: %ds\n"%(time.time()-start_time)) 48 | return 0 49 | 50 | class FindCDS: 51 | ''' 52 | Find the most like CDS in a given sequence 53 | The most like CDS is the longest ORF found in the sequence 54 | When having same length, the upstream ORF is printed 55 | modified from source code of CPAT 1.2.1 downloaded from https://sourceforge.net/projects/rna-cpat/files/?source=navbar 56 | ''' 57 | def __init__(self,seq): 58 | self.seq = seq 59 | self.result = (0,0,0,0,0) 60 | self.longest = 0 61 | self.basepair = {"A":"T","T":"A","U":"A","C":"G","G":"C","N":"N","X":"X"} 62 | 63 | def _reversecompliment(self): 64 | return "".join(self.basepair[base] for base in self.seq)[::-1] 65 | 66 | def get_codons(self,frame_number): 67 | ''' 68 | Record every nucleotide triplet and its coordinate position for input sequence in one frame 69 | ''' 70 | coordinate = frame_number 71 | while coordinate + 3 <= len(self.seq): 72 | yield (self.seq[coordinate:coordinate+3], coordinate) 73 | coordinate += 3 74 | 75 | def find_longest_in_one(self,myframe,direction,start_codon,stop_codon): 76 | ''' 77 | find the longest ORF in one reading myframe 78 | ''' 79 | triplet_got = self.get_codons(myframe) 80 | starts = start_codon 81 | stops = stop_codon 82 | ''' 83 | Extend sequence by triplet after start codon encountered 84 | End ORF extension when stop codon encountered 85 | ''' 86 | while True: 87 | try: 88 | codon,index = triplet_got.next() 89 | except StopIteration: 90 | break 91 | if codon in starts and codon not in stops: 92 | ''' 93 | find the ORF start 94 | ''' 95 | orf_start = index 96 | end_extension = False 97 | while True: 98 | try: 99 | codon,index = triplet_got.next() 100 | except StopIteration: 101 | end_extension = True 102 | integrity = -1 103 | if codon in stops: 104 | integrity = 1 105 | end_extension = True 106 | if end_extension: 107 | orf_end = index + 3 108 | Length = (orf_end - orf_start) 109 | if Length > self.longest: 110 | self.longest = Length 111 | self.result = [direction,orf_start,orf_end,Length,integrity] 112 | if Length == self.longest and orf_start < self.result[1]: 113 | ''' 114 | if ORFs have same length, return the one that if upstream 115 | ''' 116 | self.result = [direction,orf_start,orf_end,Length,integrity] 117 | break 118 | 119 | def longest_orf(self,direction,start_codon={"ATG":None}, stop_codon={"TAG":None,"TAA":None,"TGA":None}): 120 | return_orf = "" 121 | for frame in range(3): 122 | self.find_longest_in_one(frame,"+",start_codon,stop_codon) 123 | return_orf = self.seq[self.result[1]:self.result[2]][:] 124 | start_coordinate = self.result[1] 125 | strand_direction = "+" 126 | orf_integrity = self.result[4] 127 | ''' 128 | Also check reverse chain if -r is chosen 129 | ''' 130 | if direction == "-": 131 | self.seq = self._reversecompliment() 132 | for frame in range(3): 133 | self.find_longest_in_one(frame,"-",start_codon,stop_codon) 134 | if self.result[0] == "-": 135 | return_orf = self.seq[self.result[1]:self.result[2]][:] 136 | start_coordinate = self.result[1] 137 | strand_direction = "-" 138 | orf_integrity = self.result[4] 139 | return return_orf,start_coordinate,strand_direction,orf_integrity 140 | 141 | 142 | class Fickett: 143 | ''' 144 | calculate Fickett TESTCODE for full sequence 145 | NAR 10(17) 5303-531 146 | modified from source code of CPAT 1.2.1 downloaded from https://sourceforge.net/projects/rna-cpat/files/?source=navbar 147 | ''' 148 | def __init__(self): 149 | '''new compiled Fickett look-up table''' 150 | self.position_parameter = [1.9,1.8,1.7,1.6,1.5,1.4,1.3,1.2,1.1,0.0] 151 | self.content_parameter = [0.33,0.31,0.29,0.27,0.25,0.23,0.21,0.19,0.17,0] 152 | self.position_probability = { 153 | "A":[0.51,0.55,0.57,0.52,0.48,0.58,0.57,0.54,0.50,0.36], 154 | "C":[0.29,0.44,0.55,0.49,0.52,0.60,0.60,0.56,0.51,0.38], 155 | "G":[0.62,0.67,0.74,0.65,0.61,0.62,0.52,0.41,0.31,0.17], 156 | "T":[0.51,0.60,0.69,0.64,0.62,0.67,0.58,0.48,0.39,0.24], 157 | } 158 | self.position_weight = {"A":0.062,"C":0.093,"G":0.205,"T":0.154} 159 | self.content_probability = { 160 | "A":[0.40,0.55,0.58,0.58,0.52,0.48,0.45,0.45,0.38,0.19], 161 | "C":[0.50,0.63,0.59,0.50,0.46,0.45,0.47,0.56,0.59,0.33], 162 | "G":[0.21,0.40,0.47,0.50,0.52,0.56,0.57,0.52,0.44,0.23], 163 | "T":[0.30,0.49,0.56,0.53,0.48,0.48,0.52,0.57,0.60,0.51] 164 | } 165 | self.content_weight = {"A":0.084,"C":0.076,"G":0.081,"T":0.055} 166 | 167 | 168 | def look_up_position_probability(self,value, base): 169 | ''' 170 | look up positional probability by base and value 171 | ''' 172 | if float(value) < 0: 173 | return None 174 | for idx,val in enumerate (self.position_parameter): 175 | if (float(value) >= val): 176 | return float(self.position_probability[base][idx]) * float(self.position_weight[base]) 177 | 178 | def look_up_content_probability(self,value, base): 179 | ''' 180 | look up content probability by base and value 181 | ''' 182 | if float(value) < 0: 183 | return None 184 | for idx,val in enumerate (self.content_parameter): 185 | if (float(value) >= val): 186 | return float(self.content_probability[base][idx]) * float(self.content_weight[base]) 187 | 188 | def fickett_value(self,dna): 189 | ''' 190 | calculate Fickett value from full RNA transcript sequence 191 | ''' 192 | if len(dna) < 2: 193 | return 0 194 | fickett_score=0 195 | dna=dna 196 | total_base = len(dna) 197 | A_content = float(dna.count("A"))/total_base 198 | C_content = float(dna.count("C"))/total_base 199 | G_content = float(dna.count("G"))/total_base 200 | T_content = float(dna.count("T"))/total_base 201 | 202 | phase_0 = dna[::3] 203 | phase_1 = dna[1::3] 204 | phase_2 = dna[2::3] 205 | 206 | phase_0_A = phase_0.count("A") 207 | phase_1_A = phase_1.count("A") 208 | phase_2_A = phase_2.count("A") 209 | phase_0_C = phase_0.count("C") 210 | phase_1_C = phase_1.count("C") 211 | phase_2_C = phase_2.count("C") 212 | phase_0_G = phase_0.count("G") 213 | phase_1_G = phase_1.count("G") 214 | phase_2_G = phase_2.count("G") 215 | phase_0_T = phase_0.count("T") 216 | phase_1_T = phase_1.count("T") 217 | phase_2_T = phase_2.count("T") 218 | 219 | A_content = float(phase_0_A + phase_1_A + phase_2_A)/total_base 220 | C_content = float(phase_0_C + phase_1_C + phase_2_C)/total_base 221 | G_content = float(phase_0_G + phase_1_G + phase_2_G)/total_base 222 | T_content = float(phase_0_T + phase_1_T + phase_2_T)/total_base 223 | A_position= np.max([phase_0_A,phase_1_A,phase_2_A])/(np.min([phase_0_A,phase_1_A,phase_2_A]) +1.0) 224 | C_position= np.max([phase_0_C,phase_1_C,phase_2_C])/(np.min([phase_0_C,phase_1_C,phase_2_C]) +1.0) 225 | G_position= np.max([phase_0_G,phase_1_G,phase_2_G])/(np.min([phase_0_G,phase_1_G,phase_2_G]) +1.0) 226 | T_position= np.max([phase_0_T,phase_1_T,phase_2_T])/(np.min([phase_0_T,phase_1_T,phase_2_T]) +1.0) 227 | 228 | fickett_score += self.look_up_content_probability(A_content,"A") 229 | fickett_score += self.look_up_content_probability(C_content,"C") 230 | fickett_score += self.look_up_content_probability(G_content,"G") 231 | fickett_score += self.look_up_content_probability(T_content,"T") 232 | 233 | fickett_score += self.look_up_position_probability(A_position,"A") 234 | fickett_score += self.look_up_position_probability(C_position,"C") 235 | fickett_score += self.look_up_position_probability(G_position,"G") 236 | fickett_score += self.look_up_position_probability(T_position,"T") 237 | 238 | return fickett_score 239 | 240 | #=================== 241 | 242 | def mRNA_translate(mRNA): 243 | return Seq(mRNA).translate() 244 | 245 | def protein_param(putative_seqprot): 246 | return putative_seqprot.isoelectric_point() 247 | 248 | def calculate_potential(fasta,strand,output_orf,outfile): 249 | ''' 250 | Calculate three features: putative peptide length,pI and Fickett 251 | And assess coding potential based on SVM model 252 | ''' 253 | strinfoAmbiguous = re.compile("X|B|Z|J|U",re.I) 254 | ptU = re.compile("U",re.I) 255 | ftmp_feat = file(outfile + ".feat","w") 256 | ftmp_svm = file(outfile + ".tmp.1","w") 257 | ftmp_result = file(outfile,"w") 258 | if output_orf == 1: 259 | my_header = ["#ID","transcript_length","peptide_length","Fickett_score","pI","ORF_integrity","putative_peptide","coding_probability","label"] 260 | else: 261 | my_header = ["#ID","transcript_length","peptide_length","Fickett_score","pI","ORF_integrity","coding_probability","label"] 262 | ftmp_result.write("\t".join(map(str,my_header))+"\n") 263 | fickett_obj = Fickett() 264 | for seq in seqio.fasta_read(fasta): 265 | seqid = seq.id 266 | seqRNA = ptU.sub("T",str(seq.seq).strip()) 267 | '''seqRNA:transcript full sequence''' 268 | seqRNA = seqRNA.upper() 269 | seqCDS,start_pos,orf_strand,orf_fullness = FindCDS(seqRNA).longest_orf(strand) 270 | '''seqCDS:longest ORF''' 271 | seqprot = mRNA_translate(seqCDS) 272 | pep_len = len(seqprot) #pep_len = len(seqprot.strip("*")) 273 | newseqprot = strinfoAmbiguous.sub("",str(seqprot)) 274 | '''exclude ambiguous amio acid X, B, Z, J, Y in peptide sequence''' 275 | fickett_score = fickett_obj.fickett_value(seqRNA) 276 | newseqprot = str(newseqprot.strip("*")) 277 | protparam_obj = ProtParam.ProteinAnalysis(newseqprot) 278 | if pep_len > 0: 279 | #fickett_score = fickett_obj.fickett_value(seqCDS) 280 | start_pos = start_pos + 1 281 | isoelectric_point = protein_param(protparam_obj) 282 | else: 283 | #fickett_score = 0.0 284 | newseqprot = "non" 285 | start_pos = 0 286 | orf_fullness = -1 287 | isoelectric_point = 0.0 288 | if output_orf == 1: 289 | output_line = [seqid,len(seqRNA),pep_len,fickett_score,isoelectric_point,orf_fullness,newseqprot] 290 | else: 291 | output_line = [seqid,len(seqRNA),pep_len,fickett_score,isoelectric_point,orf_fullness, ""] 292 | ftmp_result.write("\t".join(map(str,output_line))+"\n") 293 | ftmp_feat.write("\t".join(map(str,[seqid,len(seqRNA),pep_len,fickett_score,isoelectric_point,orf_fullness]))+"\n") 294 | ftmp_svm.write("".join(map(str,["999"," 1:",pep_len," 2:",fickett_score," 3:",isoelectric_point," 4:",orf_fullness]))+"\n") 295 | ftmp_result.close() 296 | ftmp_feat.close() 297 | ftmp_svm.close() 298 | #return 0 299 | 300 | ''' 301 | calculate the coding probability using LIBSVM 302 | ''' 303 | sys.stderr.write("[INFO] Predicting coding potential, please wait ...\n") 304 | 305 | ''' 306 | set directories and check depending tools existance 307 | ''' 308 | script_dir,filename = os.path.split(os.path.abspath(sys.argv[0])) 309 | data_dir = script_dir + "/../data/" 310 | lib_dir = script_dir + "/../libs/" 311 | app_svm_scale = lib_dir + "libsvm/libsvm-3.18/svm-scale" 312 | app_svm_predict = lib_dir + "libsvm/libsvm-3.18/svm-predict" 313 | os.system('test -x '+ app_svm_scale + ' || echo \"[ERROR] No excutable svm-scale on CPC2 path!\" > /dev/stderr') 314 | os.system('test -x '+ app_svm_predict + ' || echo \"[ERROR] No excutable svm-predict on CPC2 path!\" > /dev/stderr') 315 | 316 | cmd = app_svm_scale + ' -r ' + data_dir + 'cpc2.range ' + outfile + '.tmp.1 > ' + outfile + '.tmp.2 &&' 317 | cmd = cmd + app_svm_predict + ' -b 1 -q ' + outfile + '.tmp.2 ' + data_dir + 'cpc2.model ' + outfile + '.tmp.out' 318 | #cmd = cmd + 'awk -vOFS="\\t" \'{if ($1 == 1){print $2,"coding"} else if ($1 == 0){print $2,"noncoding"}}\' ' + outfile + '.tmp.1 > ' + outfile + '.tmp.2 &&' 319 | #cmd = cmd + 'paste ' + outfile + '.feat ' + outfile + '.tmp.2 >>' + outfile 320 | (exitstatus, outtext) = commands.getstatusoutput(cmd) 321 | 322 | '''deal with the output''' 323 | #print outfile + '.tmp.out' 324 | tmp_file = open(outfile + '.tmp.out','r') 325 | prob = {} 326 | i = 0 327 | # get libsvm output 328 | for line in tmp_file: 329 | i = i + 1 330 | array = line.split(' ') 331 | if array[0] == "1": 332 | label = "coding" 333 | else: 334 | label = "noncoding" 335 | prob[i] = str(array[1]) + '\t' + label 336 | tmp_file.close() 337 | # paste to features 338 | tmp_file = open(outfile,'r') 339 | out_file = open(outfile + '.txt','w') 340 | i = 0 341 | for line in tmp_file: 342 | i = i + 1 343 | if i == 1: 344 | out_file.write(line) 345 | else: 346 | line = line.rstrip('\n') 347 | out_file.write(line) 348 | out_file.write('\t' + prob[i] + '\n') 349 | tmp_file.close() 350 | out_file.close() 351 | # subprocess.call("Rscript " + outfile + '.r', shell=True) 352 | #except: 353 | # pass 354 | if exitstatus == 0: 355 | os.system('rm -f ' + outfile + '.tmp.1 ' + outfile + '.tmp.2 ' + outfile + '.tmp.out ' + outfile) 356 | rm_cmd = "rm -f " + outfile + '.feat' 357 | commands.getstatusoutput(rm_cmd) 358 | sys.stderr.write("[INFO] Running Done!\n") 359 | return 0 360 | else: 361 | sys.stderr.write("[ERROR] Prediction error!\n") 362 | return -1 363 | 364 | if __name__ == "__main__": 365 | sys.exit(__main()) 366 | -------------------------------------------------------------------------------- /bin/compress.py: -------------------------------------------------------------------------------- 1 | ''' 2 | This module deals with compressed file (.gz or .bz2) 3 | ''' 4 | 5 | import gzip 6 | import bz2 7 | import sys 8 | def gz_file(fq_file,mode,level=6): 9 | try: 10 | if fq_file.endswith("gz"): 11 | fq_fp = gzip.open(fq_file,mode+"b",level) 12 | else: 13 | sys.stderr.write("[INFO] read file '%s'\n"%fq_file) 14 | fq_fp = file(fq_file,mode) 15 | except: 16 | sys.stderr.write("Error: Fail to IO file: %s\n"%(fq_file)) 17 | sys.exit(1) 18 | return fq_fp 19 | 20 | 21 | def bz2file(f): 22 | fz = None 23 | if f.endswith("bz2"): 24 | fz = bz2.BZ2File(f) 25 | else: 26 | sys.stderr.write("Error: Fail to IO file: %s\n"%(f)) 27 | sys.exit(1) 28 | return fz 29 | 30 | -------------------------------------------------------------------------------- /bin/seqio.py: -------------------------------------------------------------------------------- 1 | ''' 2 | This module deals with input or output in commom formats 3 | ''' 4 | 5 | import sys 6 | import compress 7 | import os 8 | from Bio import SeqIO 9 | 10 | def variant_snpindel_pop(total_fn): 11 | f = compress.gz_file(total_fn,"r") 12 | for line in f: 13 | if line.startswith("#"):continue 14 | chrom,position1,position2,ref,alt,qual,group_test_pvalue,depth_ref,depth_alt,depth_ref_samples,depth_alt_samples,genotype,other = line.rstrip("\n").split("\t") 15 | yield [chrom,position1,position2,ref,alt,qual,group_test_pvalue,depth_ref,depth_alt,depth_ref_samples,depth_alt_samples,genotype] 16 | f.close() 17 | 18 | 19 | def merge_region(regions): 20 | # regions must be sorted 21 | mergedregion = [] 22 | if len(regions) > 0: 23 | initstart,initend = regions[0] 24 | for start,end in regions: 25 | if start <= initend: 26 | initend = end 27 | else: 28 | mergedregion.append([initstart,initend]) 29 | initstart = start 30 | initend = end 31 | mergedregion.append([initstart,initend]) 32 | return mergedregion 33 | 34 | def arf_read(arffn): 35 | f = compress.gz_file(arffn,"r") 36 | for line in f: 37 | if line.startswith("#"):continue 38 | rname,rleng,rstart,rend,rseq,gname,gleng,gstart,gend,gseq,gstrand,nmismatch,mathclabel = line.rstrip("\n").split("\t") 39 | yield [rname,rleng,rstart,rend,rseq,gname,gleng,gstart,gend,gseq,gstrand,nmismatch,mathclabel] 40 | f.close() 41 | 42 | def fileread(fn): 43 | if not os.path.isfile(fn): 44 | sys.stderr.write("[Error] '%s' is not a file\n"%fn) 45 | exit(1) 46 | if fn.endswith(".gz"): 47 | f = compress.gz_file(fn,"r") 48 | elif fn.endswith(".bz2"): 49 | f = compress.bz2file(fn) 50 | return f 51 | 52 | def bed6_parse(fn): 53 | f = compress.gz_file(fn,"r") 54 | for line in f: 55 | if line.startswith("#"):continue 56 | chrom,start,end,name,score,strandother = line.rstrip().split("\t",5) 57 | yield [chrom,start,end,name,score,strandother] 58 | f.close() 59 | 60 | def gff3_parse(fn): 61 | f = compress.gz_file(fn,"r") 62 | for line in f: 63 | if line.startswith("#"):continue 64 | chrom,source,seqtype,start,end,score,strand,phase,attributes = line.rstrip("\n").split("\t") 65 | yield [chrom,source,seqtype,start,end,score,strand,phase,attributes] 66 | f.close() 67 | 68 | def refgene_parse(fn): 69 | f = compress.gz_file(fn,"r") 70 | for line in f: 71 | if line.startswith("#"):continue 72 | num,nm_name,chrom,strand,exon_s,exon_e,cds_s,cds_e,exon_num,exonstarts,exonends,uniq_id,symbol, kown1, kown2, exon_status = line.rstrip().split("\t") 73 | yield[num,nm_name,chrom,strand,exon_s,exon_e,cds_s,cds_e,exon_num,exonstarts,exonends,uniq_id,symbol, kown1, kown2, exon_status] 74 | f.close() 75 | 76 | def miRNA_target_parse(fn): 77 | f = compress.gz_file(fn,"r") 78 | for line in f: 79 | if line.startswith("#"):continue 80 | arr = line.rstrip("\n").split("\t") 81 | microRNAid,detalmciroRNA,target_Genes = arr[0:3] 82 | UTR = arr[-3] 83 | pairing = arr[-2] 84 | miseq = arr[-1] 85 | yield[microRNAid,detalmciroRNA,target_Genes,UTR,pairing,miseq] 86 | f.close() 87 | 88 | 89 | def sigfile_parse(fn): 90 | f = compress.gz_file(fn,"r") 91 | for line in f: 92 | if line.startswith("#"):continue 93 | anno1,anno2,fc,rawp,fdr = line.rstrip("\n").split("\t") 94 | yield [anno1,anno2,fc,rawp,fdr] 95 | f.close() 96 | 97 | def soap_aln_parse(fn): 98 | f = compress.gz_file(fn,"r") 99 | for line in f: 100 | if line.startswith("#"):continue 101 | seqid,seqread,qual,mcounts,PEtag,length,strand,chrom,sitestart1,mismatch,cigar,match = line.rstrip("\n").split("\t") 102 | yield [seqid,seqread,qual,mcounts,PEtag,length,strand,chrom,sitestart1,mismatch,cigar,match] 103 | f.close() 104 | 105 | def fasta_read(fn): 106 | """ 107 | ID: gi|2765658|emb|Z78533.1|CIZ78533 108 | Name: gi|2765658|emb|Z78533.1|CIZ78533 109 | Description: gi|2765658|emb|Z78533.1|CIZ78533 C.irapeanum 5.8S rRNA gene and ITS1 and ITS2 DNA 110 | Number of features: 0 111 | Seq('CGTAACAAGGTTTCCGTAGGTGAACCTGCGGAAGGATCATTGATGAGACCGTGG...GGG', SingleLetterAlphabet()) 112 | """ 113 | f = compress.gz_file(fn,"r") 114 | for seq in SeqIO.parse(f,"fasta"): 115 | yield seq 116 | f.close() 117 | 118 | def fastq_read(fn,qual): 119 | if qual not in ['fastq-sanger','fastq-solexa','fastq-illumina']: 120 | sys.stderr.write("[ERROR] Unknown quality\n") 121 | exit(1) 122 | 123 | f = fileread(fn) 124 | """ 125 | rec.seq 126 | rec.letter_annotations['phred_quality'] 127 | """ 128 | for seq in SeqIO.parse(f,qual): 129 | yield seq 130 | f.close() 131 | 132 | def bwt_parse(fn): 133 | f = compress.gz_file(fn,"r") 134 | for line in f: 135 | query_id,strand,subject_id,pos,seq,qual,score,mismatch = line.rstrip("\n").split("\t") 136 | yield [query_id,strand,subject_id,pos,seq,qual,score,mismatch] 137 | f.close() 138 | 139 | def blast6_parse(fn): 140 | f = compress.gz_file(fn,"r") 141 | for line in f: 142 | if line.startswith("#"):continue 143 | try: 144 | query_id, subject_id, identity, alignment_length, mismatches, gap_opens, qstart, qend, sstart, send, evalue, bitscore = line.rstrip("\n").split("\t") 145 | except: 146 | sys.stderr.write("[WARN] blast can not parse '%s'"%line) 147 | continue 148 | yield [query_id, subject_id, identity, alignment_length, mismatches, gap_opens, qstart, qend, sstart, send, evalue, bitscore] 149 | f.close() 150 | 151 | def gtf_parse(fn,add="chr"): 152 | f = compress.gz_file(fn,"r") 153 | for line in f: 154 | if line.startswith("#"):continue 155 | chrom,rnatype,region_type,start,end,score,strand,codon,commnet = line.rstrip("\n").split("\t") 156 | yield[add+chrom.lstrip("chr"),rnatype,region_type,start,end,score,strand,codon,commnet] 157 | f.close() 158 | 159 | ## def blast_parse 160 | ## def sam or bam parse ... 161 | ## 162 | 163 | if __name__ == "__main__": 164 | a = [[1,10],[17,22],[40,44],[42,47],[46,100],[101,408]] 165 | print a 166 | print merge_region(a) 167 | 168 | 169 | 170 | -------------------------------------------------------------------------------- /data/cpc2.range: -------------------------------------------------------------------------------- 1 | x 2 | -1 1 3 | 1 0 14507 4 | 2 0.22328 0.51262 5 | 3 0 13.2714233398 6 | 4 -1 1 7 | -------------------------------------------------------------------------------- /data/example.fa: -------------------------------------------------------------------------------- 1 | >AF282387 Filobasidiella neoformans calcineurin B regulatory subunit (CNB1) mRNA, complete cds 2 | ATGGGTGCCGCTGAATCCTCCATGTTCAACTCTCTGGAGAAGAACTCCAACTTCTCAGGACCGGAGCTTA 3 | TGAGGTTGAAGAAGAGGTTCATGAAGCTTGACAAGGACGGTTCCGGATCGATTGACAAAGACGAGTTTCT 4 | TCAGATCCCTCAAATCGCGAATAACCCTTTGGCGCATCGAATGATAGCAATCTTTGATGAAGATGGAAGT 5 | GGAACGGTTGACTTCCAAGAATTTGTCGGAGGTTTGAGCGCTTTCAGTAGTAAAGGAGGTCGTGATGAGA 6 | AGCTGAGATTCGCTTTCAAGGTGTACGACATGGATCGAGACGGCTACATCTCTAACGGTGAACTGTATCT 7 | TGTGTTGAAGCAAATGGTCGGAAATAACCTTAAAGACCAACAATTGCAACAAATTGTAGACAAAACCATC 8 | ATGGAGGCTGACAAGGACGGGGATGGAAAGCTCTCTTTTGAGGAGTTCACACAAATGGTCGCCAGCACAG 9 | ATATTGTGAAGCAAATGACCCTTGAAGATCTTTTCTAA 10 | 11 | >Tsix_mus NR_002844.1 Mus musculus X (inactive)-specific transcript, antisense (Tsix) on chromosome X 12 | GTGTGTTCATGCGTGCGCACGTGTACCCGTGCGTCCACACTCCGCCAGCACGTGTGCTAGCTTGCAAGTT 13 | TTCAGTTTGAGTACAGACACCAGGCCATAGCCCAATGGCAGCAGTGACAGGGAGGACCGTGGCAGCATGT 14 | TACAATCAGAAGACAACTTCCGGATTTTCACTCTGTCCTAAAAAGGTGGTCAAGTGTGCTAACCACACCC 15 | TCTCAGCAGGATCCCGCGCCTCAAGAGCCTTAGGTCCCGCCCCACACTCCCTCAAACCCTCAGTGCAGCG 16 | CTTGTGTCAGGCGCAATCTCGCAAGATCCGGTGAGGCGCTACGTCGTGCTCCACTCGGTCCCAAAAGTAC 17 | CTGCAAGCGCTACACACTTGCGCTCGGCGCCCTTGCTCTGTTCTCACTTTCCGAGATATCCACGCATCTT 18 | GAGTCCTGCATCCACTCCCGGGAGGCGGCTGCGGCAAGCGCGTGATGGAAGAAGAGCGTGATAGCCAGCT 19 | AGACAGGTGGCCAGAGCGGAGCGGACAGTGGAGCGATGGCTACGTGCTTGCGGGACAGCGGAAGAGATGG 20 | TTAAAGTGATTGCCAAGCAGCAGAAAGATTCCTAAAATGCTTGCCAGCTATGCGGAGATGAAGGTGAGGT 21 | TTCAATGATTTACATCGACCAAGAACCCGCAGCCTCGGTCTCTCGAATCGGATCCGACATCATCCAACAC 22 | TTCAGTGTTAGAATTGCAAGCATGCGCTCTCCCGACCTGGGCAGGCACTTCGAAAAAATGATGACTAAAG 23 | ACACACGTGAAGTACCAAGCGAAACTCACGTCCTTATGGGACAGTGACTCATCACAGTCTAATTCCATCC 24 | TGGCCACCAAGCAATAATGCACATTTCTAACTGGAAGTCAAGCAAACACCAACACTTTCACACTTGTGCC 25 | CATTTCTGACGAGTTACGTCAAGTGGCAACCAACACTTCCACTTAGCCTTGCCTCAGCTTCGAGTGGCAC 26 | AAGGTAGGACCAACCACACCCTACCATAATGCACCAAGTGTACCCTCGGGCAAAGCCCGCCAAGTAGCTA 27 | AAGCCCGCCAAAAAAAAAATCACTGAAAGAAACCACTAGAGGGCAGGTCACATGACTTCCGCCATCTTAG 28 | ACACATTCAAGAGCATGTGCCACCTCTCCAGGCTAACTCAGACATGAAGCTGACATGTGACACACAAAGC 29 | CCTTTGCGTTATACCGCACCAAGAACTTGAGCCGCCATCTTTTCCTGTACGACCTAAATGTCCTATAATC 30 | CATTGCTACACACCAGAACAAAGATTGGGCTGTCGAGCCTCGGGTGGAGCCCCCGAGCCGCCATTTTATA 31 | GACTTCTGAGCAGCCCTTAAAGCCACGGGGGACCGCGCCAGGGGTCCATATGCACACACACCCTGCCCAA 32 | TCCCCACACCCACGCTGAGCCCTATCCCCTAGTCCTCTGCGGCTTCCGCGCAACACCGCACACTAATACG 33 | AGCACTCCTTGGCTTTCTCTTCCGGCTAGCACAACCCCGCAAATGCTACCACAAATCAAGGCGAATCCCG 34 | CAACCCCGCACATATAAAGAAAGCCTTTAGCTAGCGCAGCGCAATTGGTTGCTTTTATCCAGTCCGCTGT 35 | GCTCCTCGGTGTCCTAATTCTTGGCGTAACTGGCTCGAGAATAGCCGTATCACGCAGAAGCCATAATGGC 36 | GGACGCGGGCTCTCCACGCCCTGAACACCCACTCAGTTTAAGAGCAAAGTCGTTTTTCTAAGCCATAGGT 37 | TCACTCACACAGCACCAAACGATCAGCAGCAACAGTACACGCAAATAAGAGGCATAGATATTCCAGGTAG 38 | TGCAATAACTCACAAAACCATATTTCCATCCACCAAGCCCCGTTGGGCCTGTAAAAAAAAAATTTAAAGC 39 | AGGTATCCACAGCCCCGATGGGCAAAAGAAAAAGAAAAAAAAATAATAACAGCAGGTATCCGAGGCCCCG 40 | TTGGGCATGGGAAAAAAAGACTAAACGCAGGTATCCGAGGTCCCGATGGACCGAGAAAGGTTTTTTTTTT 41 | TTTTTTTTTTTTTACAAAAAGCAGGTATCCATGGCCCCGATGGGCTAAGGAGAAGAAAAAAAGAATAAAA 42 | GCAGGTATCCACAGCCCAGATGGGCAAGTTTAGAAAAAAAAATAATAAGAAAAAAAAAGAATGAAAAGGC 43 | AGGTAAGTATCCAAAACCCCGTTGGGCATGGAATGGCGGGGAGGACACACAGGTATCCGTGGCCCCGATG 44 | GGCAAGATTATATAAACAATGAAAGAAAGGTAAGTCCACCATACACACACAAGTATCAACCAAAAGGCAC 45 | AACAAAGAAATATTCCTTAAAAATGAAAAATTGACTGAAAATATTACAAATATCAAAAAGTATGGAGGAC 46 | ATGTCAAAAAAAAAATCTTACCAGAACATATCAAAACGTCAAAAATCTCGTGGAATTTTGATATGTTTTC 47 | TTAAATAAGCCATAAGGCTTGGTGGTAGGGGAACTAAAAATGTTCCCCCAAAGCTCCTTAGATGGAGAGA 48 | AACCACGGAAGAACCGCACATCCACGGGAAACGAGCAAACATGGCTGGAGCAAGCCGTTGCACGCCTTTA 49 | ACTGATCCGCGGCGCTGAAGGCGGAGAGACCAGAAGAGGAGTGGCCACAAAGATTGCAATTCTGACATCT 50 | TATTGGACCTTTAGGTCTAACTATATTATAAAAAAATTAAAATGAATAAAGATGGAGGTACGTAAGCTCA 51 | GTGACATGACGCGTGAATTTCATTATTTTGCGCGATAATGAAGGATTATCCTATTTTACAGCTAAAAACG 52 | TTTATGTAGAACTTCACATAAACATTTGGGTGTGTACATTTAGCACACACCTGTCTATGCAAAATTTCAA 53 | TATATCTTCTACTTGGACAAACCATGTGTCGCTCCGGTCTTGGACACTAGAAGTTCTTCTGCATTAGTTG 54 | GCGACCTCAGATGAGGAGAGGAAAGGGTAGAAATGCCTCACAAAATGGCTCCTTGGTTCCTAAATTATCA 55 | GAGTATTAGTTGTGACCGATTTGGAGGGCTTACGCTCATAGTTTTGGGTCATTGGCATCTTAGTCTTTCT 56 | CTGGGAACCTGGTGACTCCATACCTTGGGACAAAAACGCACTGAAGACGTTACTAGCTAGCAGTAATGAA 57 | AAATAATTCCTAAATGCCAAAGCAAAGCCTTAGGGAATAATAGCTCATTGGTATCTTACTCGCCCCAGAG 58 | ACACTGCTAACTTAAAAGAACTGTCAAATTTTGTTAACTGTCAAACTATGAATATCCACATGAAAGAGAT 59 | CAGACACCCTGGGTATTAGAAAATCAAAGGATATGTTGTCTCGTTGATCACGCTGACAAATAATTCACAG 60 | TCTGTTCTAAGTTCCCTTTAGGCGTCCCATGAATAATAAAGGACACAAAATTGGTTTGCTTATGGACGAT 61 | CAAAGTGCCAGCAATTCAGTAATCTTACTATTGAGGTGGTTCAGGTAGGGATGGAAAAATATCTGCTACA 62 | AAATAAACAGTTTCAACCAAAAGAAAAACAAATTAACAAGGTAAATAAATGATGCACACAGACTGAATAA 63 | ACCAGCAGGTGGCAGCATGAATCTTTCCAAGGCATCTGAAGCCAAACTTGGAGTGCAAAAGGATTCCTAT 64 | CTGAATTGAGAAGTAAAGGTTACTTTGTCTAACTTTAGTTGACAGAGCGATCAGGATCAGAGTAACAAGC 65 | ACACCAAAAGCATCACCAGTGAGAAGTCACATAGGACATATTAGGGAAAAAAGACCCAAGGAAGGGCTCT 66 | TCACAGCTAAGAGCACCTGGCTCCACGATGGATATGGCTTTGTATAAACGAGAACTTCTAAATGAGCTGT 67 | ACAAAGAGAATTTAGAACTTGCGAGGTACTGGTCACAGATTATGCAAGCCAGTGTATCATTTTTGTGGGG 68 | ATGCTAGAGAGAATCATCAAATTAAAGAGTTAAATTTAGTCTCTGTGTTTTACTTAGTCCCAATTCTTGC 69 | AAAGGTCATCATTCTTTCTCACACCGTGTACATCAAGGTATGTCAGGTTTCGGGGACACTTTTTAGTCTT 70 | ATCACAAGAAAGCATGAAGGGATATGTGCTAAAACTCAGTTCCTGGGCTGGAGAGATAGCTCAGTGGTTA 71 | GGAGTGCTGACTGCTCTTCCAGAGGGCCTGAGTTCAATTCTCAACAACTTCGTTGTGGCTCACAGTCATC 72 | TGTAGTGGGGGATCCGATATCTAACCTTCTTCTGATGTATCTGAACAGTGACCGACAGTGTACTCACATT 73 | AAATAAATATTTTTCTAAAAAACACCTCCA 74 | -------------------------------------------------------------------------------- /libs/libsvm/libsvm-3.18.tar.gz: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/gao-lab/CPC2_standalone/53ba517309aad8ddb1054c13ea93d6781ce3dfe8/libs/libsvm/libsvm-3.18.tar.gz --------------------------------------------------------------------------------