├── CHANGES.txt ├── LICENSE.txt ├── MANIFEST.in ├── README.rst ├── data ├── genelists.txt ├── gl01 ├── gl02 ├── gl03 ├── gl04 ├── gl05 └── gl06 ├── dist ├── sharepathway-0.2.1.tar.gz ├── sharepathway-0.2.2.tar.gz ├── sharepathway-0.2.3.tar.gz ├── sharepathway-0.3.0.tar.gz ├── sharepathway-0.4.0.zip ├── sharepathway-0.4.1.zip ├── sharepathway-0.4.2.zip └── sharepathway-0.5.0.zip ├── setup.py ├── sharepathway.egg-info ├── PKG-INFO ├── SOURCES.txt ├── dependency_links.txt ├── requires.txt └── top_level.txt └── sharepathway ├── __init__.py ├── __init__.pyc ├── __pycache__ ├── __init__.cpython-33.pyc ├── enrichment.cpython-33.pyc ├── geneIDconv.cpython-33.pyc ├── genes2mat.cpython-33.pyc ├── linkpath2mat.cpython-33.pyc ├── out2html.cpython-33.pyc ├── parse_kegg.cpython-33.pyc ├── readfiles.cpython-33.pyc └── run.cpython-33.pyc ├── correct_pvalues.py ├── enrichment.py ├── enrichment.pyc ├── geneIDconv.py ├── geneIDconv.pyc ├── genes2mat.py ├── genes2mat.pyc ├── linkpath2mat.py ├── linkpath2mat.pyc ├── out2html.py ├── out2html.pyc ├── parse_kegg.py ├── parse_kegg.pyc ├── readfiles.py ├── run.py ├── run.pyc └── test └── __init__.py /CHANGES.txt: -------------------------------------------------------------------------------- 1 | v0.1.0, 2014-03-12 -- Initial release 2 | v0.1.1, 2014-05-10 -- Fix a bug 3 | v0.2.0, 2014-06-10 -- Fix a bug 4 | v0.2.3, 2014-09-22 -- add cdnjs, add pathway name in the html output, solve the p-value precision problem 5 | v0.3.0, 2014-09-23 -- support for both python2 and python3 6 | v0.4.0, 2014-10-15 -- support reading gene lists inside python, add a parameter "glist" in run.py 7 | v0.4.1, 2014-10-15 -- return enrich result for next analysis 8 | v0.4.2, 2014-10-15 -- fix a bug of gene id, new format of test-output, change the number of bacground genes 9 | v0.5.0, 2014-12-29 -- add columns description in readme 10 | -------------------------------------------------------------------------------- /LICENSE.txt: -------------------------------------------------------------------------------- 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 | {one line to give the program's name and a brief idea of what it does.} 635 | Copyright (C) {year} {name of author} 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 | {project} Copyright (C) {year} {fullname} 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 | . -------------------------------------------------------------------------------- /MANIFEST.in: -------------------------------------------------------------------------------- 1 | include README.rst *.txt setup.py -------------------------------------------------------------------------------- /README.rst: -------------------------------------------------------------------------------- 1 | SharePathway 2 | ============ 3 | 4 | SharePathway is a python package for KEGG pathway enrichment analysis with multiple gene lists. 5 | 6 | There have been dozens of tools or web servers for enrichment analysis using a list of candidate genes from some kinds of high throughput experiments,such as Exome-Seq and RNA-Seq. But the reality is that we usually get multiple gene lists, each from one sample or patient. We can do enrichment analysis for each sample then check which pathway or module is enriched. This strategy is simple and commonly used in cancer study. But we may lose some important driver genes. 7 | 8 | SharePathway is motivated at providing users a simple and easy-to-use tool for enrichment analysis on multiple lists of genes simultaneously, which may help gain insight into the underlying biological background of these lists of genes. 9 | 10 | Installation 11 | ------------ 12 | 13 | This version is for both python2 and python3. 14 | The first step is to install Python. Python is available from the `Python project page `_ . The next step is install sharepathway. 15 | 16 | Install from PyPi using `pip `_, a 17 | package manager for Python:: 18 | 19 | $ pip install sharepathway 20 | 21 | Or, you can download the source code at `Github `_ or at `PyPi `_ for SharePathway, and then run:: 22 | 23 | $ python setup.py install 24 | 25 | Usage 26 | ----- 27 | 28 | Assume you have put all the path of your gene list files in one summary file genelists.txt (one path per line) in the directory ~/data/. Go into this directory,open python and run the scripts below. The result will be saved in the result.html file:: 29 | 30 | import sharepathway as sp 31 | filein="genelists.txt" 32 | fileout="result" 33 | sp.Run(fi=filein,fo=fileout,species='hsa',r=0.1) 34 | 35 | The default value of species is 'hsa', represents human species. 36 | The ratio r is the min threshold. The default value is 0.01. 37 | Entrez Gene ID is supported. The result will be output to a html file. 38 | 39 | 40 | Output Description 41 | ------------------ 42 | 43 | * *Summary* 44 | 45 | This part summarizes the input data. 46 | 47 | * *Details* 48 | 49 | This part list the ranked pathways and related information as shown below. 50 | 51 | ======= =========== 52 | Column Description 53 | ======= =========== 54 | Pathway Pathway name and hyperlink to modified KEGG map 55 | Genes KEGG ID of the genes in the pathway 56 | pCount Total number of genes in the pathway 57 | Count The number of recognized genes from user input 58 | Ratio The percentage of lists that containing genes in the pathway 59 | Pvalue The combined p valude from Fisher's Method 60 | EASE EASE score defined by DAVID, from merged gene list 61 | FET P value of the Fisher Exact Test, from merged gene list 62 | Samples The number of genes in the pathway in each list 63 | ======= =========== 64 | 65 | 66 | Test data 67 | --------- 68 | 69 | See the gene list files and genelists.txt file in data/. This is just toy data. 70 | 71 | 72 | Contact 73 | ------- 74 | 75 | Author: Guipeng Li 76 | 77 | Email: guipeng.lee(AT)gmail.com 78 | -------------------------------------------------------------------------------- /data/genelists.txt: -------------------------------------------------------------------------------- 1 | gl03 2 | gl05 3 | gl04 4 | gl01 5 | gl02 6 | gl06 7 | -------------------------------------------------------------------------------- /data/gl01: -------------------------------------------------------------------------------- 1 | 10000 2 | 1017 3 | 1019 4 | 1021 5 | 1026 6 | 1027 7 | 1029 8 | 10297 9 | 1030 10 | 10319 11 | 10342 12 | 1050 13 | 10928 14 | 11186 15 | 11211 16 | 112398 17 | 112399 18 | 112401 19 | 1147 20 | 1163 21 | 1164 22 | 1282 23 | 1284 24 | 1285 25 | 1286 26 | 1287 27 | 1288 28 | 1387 29 | 1398 30 | 2246 31 | 2247 32 | 2248 33 | 2249 34 | 2250 35 | 2251 36 | 2252 37 | 2253 38 | 2254 39 | 2255 40 | 2256 41 | 2257 42 | 2258 43 | 2259 44 | 2260 45 | 2261 46 | 2263 47 | 2271 48 | 2277 49 | 22798 50 | 2308 51 | 2322 52 | 2323 53 | 2335 54 | 2353 55 | 23533 56 | 23604 57 | 23624 58 | 2475 59 | 25 60 | 2535 61 | 26060 62 | 26281 63 | 26291 64 | 27006 65 | 27148 66 | 2735 67 | 2736 68 | 2737 69 | 284217 70 | 2885 71 | 29119 72 | 2932 73 | 2950 74 | 2956 75 | 3065 76 | 3066 77 | 3082 78 | 3091 79 | 324 80 | 3265 81 | 329 82 | 330 83 | 331 84 | 332 85 | 3320 86 | 3326 87 | 3479 88 | 3480 89 | 354 90 | 355 91 | 3551 92 | 356 93 | 3569 94 | 3576 95 | 3655 96 | 367 97 | 3673 98 | 3674 99 | 3675 100 | 3685 101 | 3688 102 | 369 103 | 3716 104 | 3725 105 | 3728 106 | 107 | -------------------------------------------------------------------------------- /data/gl02: -------------------------------------------------------------------------------- 1 | 10000 2 | 1017 3 | 1019 4 | 1021 5 | 1026 6 | 1027 7 | 1029 8 | 10297 9 | 1030 10 | 10319 11 | 10342 12 | 1050 13 | 10928 14 | 11186 15 | 11211 16 | 112398 17 | 112399 18 | 112401 19 | 1147 20 | 1163 21 | 1164 22 | 1282 23 | 1284 24 | 1285 25 | 1286 26 | 1287 27 | 1288 28 | 1387 29 | 1398 30 | 1399 31 | 1436 32 | 1438 33 | 1441 34 | 1487 35 | 1488 36 | 1495 37 | 1496 38 | 1499 39 | 1612 40 | 1613 41 | 1630 42 | 1855 43 | 1856 44 | 1857 45 | 1869 46 | 1870 47 | 1871 48 | 1950 49 | 1956 50 | 2033 51 | 2034 52 | 2064 53 | 207 54 | 208 55 | 2113 56 | 2122 57 | 2246 58 | 2247 59 | 2248 60 | 2249 61 | 2250 62 | 2251 63 | 2252 64 | 2253 65 | 2254 66 | 2255 67 | 2256 68 | 2257 69 | 2258 70 | 2475 71 | 25 72 | 2535 73 | 26060 74 | 26281 75 | 26291 76 | 27006 77 | 27148 78 | 2735 79 | 2736 80 | 2737 81 | 284217 82 | 2885 83 | 29119 84 | 2932 85 | 2950 86 | 2956 87 | 3685 88 | 3688 89 | 369 90 | 3716 91 | 3725 92 | 3728 93 | 3815 94 | 3845 95 | 387 96 | 3908 97 | 3909 98 | 3910 99 | 3911 100 | 3912 101 | 3913 102 | 3914 103 | 3915 104 | 3918 105 | 405 106 | 4087 107 | 4088 108 | 4089 109 | 4149 110 | 4193 111 | 4233 112 | 4254 113 | 4286 114 | 4292 115 | 4312 116 | 6256 117 | 6257 118 | 6258 119 | 637 120 | 64399 121 | 6469 122 | 650 123 | 6502 124 | 7184 125 | 7185 126 | -------------------------------------------------------------------------------- /data/gl03: -------------------------------------------------------------------------------- 1 | 112401 2 | 1147 3 | 1163 4 | 1164 5 | 1282 6 | 1284 7 | 1285 8 | 1286 9 | 1287 10 | 1288 11 | 1387 12 | 1398 13 | 1399 14 | 1436 15 | 1438 16 | 1441 17 | 1487 18 | 1488 19 | 1495 20 | 1496 21 | 1499 22 | 1612 23 | 1613 24 | 1630 25 | 1855 26 | 1856 27 | 1857 28 | 1869 29 | 1870 30 | 1871 31 | 1950 32 | 1956 33 | 2033 34 | 2034 35 | 2064 36 | 207 37 | 208 38 | 2113 39 | 2122 40 | 2246 41 | 2247 42 | 2248 43 | 2249 44 | 2250 45 | 2251 46 | 2252 47 | 2253 48 | 2254 49 | 2255 50 | 2256 51 | 2257 52 | 2258 53 | 2259 54 | 2260 55 | 2261 56 | 2263 57 | 2271 58 | 2277 59 | 22798 60 | 2308 61 | 2322 62 | 2323 63 | 2335 64 | 2353 65 | 23533 66 | 23604 67 | 23624 68 | 2475 69 | 25 70 | 2535 71 | 26060 72 | 26281 73 | 26291 74 | 27006 75 | 27148 76 | 2735 77 | 2736 78 | 2737 79 | 284217 80 | 2885 81 | 29119 82 | 2932 83 | 2950 84 | 2956 85 | 3065 86 | 3066 87 | 3082 88 | 3091 89 | 324 90 | 3265 91 | 329 92 | 330 93 | 331 94 | 332 95 | 3320 96 | 3326 97 | 3479 98 | 3480 99 | 354 100 | 355 101 | 3551 102 | 356 103 | 3569 104 | 4233 105 | 4254 106 | 4286 107 | 4292 108 | 4312 109 | 4313 110 | 4318 111 | 4436 112 | 4437 113 | 4609 114 | 4790 115 | 4791 116 | 4792 117 | 4824 118 | 4843 119 | 4893 120 | 4914 121 | 51176 122 | 51384 123 | 5154 124 | 5155 125 | 5156 126 | 5159 127 | 51684 128 | 5228 129 | 5290 130 | 5291 131 | 5293 132 | 5294 133 | 5295 134 | 5296 135 | 5335 136 | 5336 137 | 5337 138 | 5371 139 | 54205 140 | 54361 141 | 54583 142 | 5467 143 | 5468 144 | 5578 145 | 5579 146 | 5582 147 | 5594 148 | 5595 149 | 5599 150 | 5601 151 | 6777 152 | 6789 153 | 6921 154 | 6923 155 | 6932 156 | 6934 157 | 7039 158 | 159 | -------------------------------------------------------------------------------- /data/gl04: -------------------------------------------------------------------------------- 1 | 10000 2 | 1017 3 | 1029 4 | 10297 5 | 11211 6 | 112398 7 | 112399 8 | 112401 9 | 1147 10 | 1163 11 | 1164 12 | 1284 13 | 1285 14 | 1286 15 | 1436 16 | 1438 17 | 1441 18 | 1487 19 | 1488 20 | 1495 21 | 1496 22 | 1870 23 | 1871 24 | 1950 25 | 1956 26 | 2033 27 | 2034 28 | 2064 29 | 207 30 | 208 31 | 2113 32 | 2122 33 | 2246 34 | 2247 35 | 2535 36 | 26060 37 | 26281 38 | 26291 39 | 27006 40 | 27148 41 | 2735 42 | 2736 43 | 2737 44 | 284217 45 | 2885 46 | 29119 47 | 2932 48 | 2950 49 | 3066 50 | 3082 51 | 3091 52 | 324 53 | 3265 54 | 329 55 | 330 56 | 331 57 | 332 58 | 3320 59 | 3326 60 | 3479 61 | 3480 62 | 354 63 | 355 64 | 3551 65 | 356 66 | 3569 67 | 3576 68 | 3655 69 | 367 70 | 3673 71 | 369 72 | 3716 73 | 3725 74 | 3728 75 | 3815 76 | 3845 77 | 387 78 | 3908 79 | 3909 80 | 3910 81 | 3911 82 | 3912 83 | 3913 84 | 3914 85 | 3915 86 | 3918 87 | 405 88 | 4087 89 | 4088 90 | 4089 91 | 4286 92 | 4292 93 | 4312 94 | 4313 95 | 4318 96 | 4436 97 | 4437 98 | 4609 99 | 4790 100 | 4791 101 | 4792 102 | 4824 103 | 4843 104 | 4893 105 | 4914 106 | 51176 107 | 51384 108 | 5154 109 | 5155 110 | 5156 111 | 5159 112 | 51684 113 | 5228 114 | 5290 115 | 5291 116 | 5293 117 | 5294 118 | 5295 119 | 5296 120 | 5335 121 | 5336 122 | 5337 123 | 5371 124 | 54205 125 | 54361 126 | 54583 127 | 5467 128 | 5468 129 | 5578 130 | 5579 131 | 5582 132 | 5602 133 | 5604 134 | 5605 135 | 572 136 | 5727 137 | 5728 138 | 5743 139 | 5747 140 | 581 141 | 5879 142 | 5880 143 | 6256 144 | 6257 145 | 6258 146 | 637 147 | 64399 148 | 6469 149 | 650 150 | 6502 151 | 6513 152 | 652 153 | 6608 154 | 6654 155 | 6655 156 | 6688 157 | 673 158 | 675 159 | 6772 160 | 6774 161 | 6776 162 | 6777 163 | 6789 164 | 6921 165 | 7040 166 | 7042 167 | 7043 168 | 7046 169 | 7048 170 | 7157 171 | 7170 172 | 173 | -------------------------------------------------------------------------------- /data/gl05: -------------------------------------------------------------------------------- 1 | 1029 2 | 10297 3 | 1030 4 | 10319 5 | 10342 6 | 1050 7 | 10928 8 | 11186 9 | 11211 10 | 112398 11 | 112399 12 | 112401 13 | 1147 14 | 1163 15 | 1164 16 | 1282 17 | 1284 18 | 1285 19 | 1286 20 | 1287 21 | 1288 22 | 23 | -------------------------------------------------------------------------------- /data/gl06: -------------------------------------------------------------------------------- 1 | 1029 2 | 10297 3 | 1030 4 | 10928 5 | 11186 6 | 11211 7 | 112398 8 | 112399 9 | 1284 10 | 1285 11 | 1286 12 | 1287 13 | 1288 14 | 15 | -------------------------------------------------------------------------------- /dist/sharepathway-0.2.1.tar.gz: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/GuipengLi/SharePathway/95bed351eb9e860a765bb1d72064a56a8879f29f/dist/sharepathway-0.2.1.tar.gz 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-------------------------------------------------------------------------------- /dist/sharepathway-0.5.0.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/GuipengLi/SharePathway/95bed351eb9e860a765bb1d72064a56a8879f29f/dist/sharepathway-0.5.0.zip -------------------------------------------------------------------------------- /setup.py: -------------------------------------------------------------------------------- 1 | from setuptools import setup 2 | 3 | setup( 4 | name = 'sharepathway', 5 | packages = ['sharepathway'], # this must be the same as the name above 6 | version = '0.5.0', 7 | description = 'A Python package for KEGG pathway enrichment analysis with multiple gene lists', 8 | author = 'Guipeng Li', 9 | author_email = 'guipenglee@gmail.com', 10 | url = 'https://github.com/GuipengLi/sharepathway', # use the URL to the github repo 11 | keywords = ['detection', 'pathway', 'enrichment', 'share', 'multiple gene lists'], # arbitrary keywords 12 | classifiers = [], 13 | long_description=open('README.rst').read(), 14 | include_package_data=True, 15 | install_requires=["numpy >= 1.4.0", "scipy >= 0.9.0"], 16 | ) 17 | -------------------------------------------------------------------------------- /sharepathway.egg-info/PKG-INFO: -------------------------------------------------------------------------------- 1 | Metadata-Version: 1.0 2 | Name: sharepathway 3 | Version: 0.5.0 4 | Summary: A Python package for KEGG pathway enrichment analysis with multiple gene lists 5 | Home-page: https://github.com/GuipengLi/sharepathway 6 | Author: Guipeng Li 7 | Author-email: guipenglee@gmail.com 8 | License: UNKNOWN 9 | Description: SharePathway 10 | ============ 11 | 12 | SharePathway is a python package for KEGG pathway enrichment analysis with multiple gene lists. 13 | 14 | There have been dozens of tools or web servers for enrichment analysis using a list of candidate genes from some kinds of high throughput experiments,such as Exome-Seq and RNA-Seq. But the reality is that we usually get multiple gene lists, each from one sample or patient. We can do enrichment analysis for each sample then check which pathway or module is enriched. This strategy is simple and commonly used in cancer study. But we may lose some important driver genes. 15 | 16 | SharePathway is motivated at providing users a simple and easy-to-use tool for enrichment analysis on multiple lists of genes simultaneously, which may help gain insight into the underlying biological background of these lists of genes. 17 | 18 | Installation 19 | ------------ 20 | 21 | This version is for both python2 and python3. 22 | The first step is to install Python. Python is available from the `Python project page `_ . The next step is install sharepathway. 23 | 24 | Install from PyPi using `pip `_, a 25 | package manager for Python:: 26 | 27 | $ pip install sharepathway 28 | 29 | Or, you can download the source code at `Github `_ or at `PyPi `_ for SharePathway, and then run:: 30 | 31 | $ python setup.py install 32 | 33 | Usage 34 | ----- 35 | 36 | Assume you have put all the path of your gene list files in one summary file genelists.txt (one path per line) in the directory ~/data/. Go into this directory,open python and run the scripts below. The result will be saved in the result.html file:: 37 | 38 | import sharepathway as sp 39 | filein="genelists.txt" 40 | fileout="result" 41 | sp.Run(fi=filein,fo=fileout,species='hsa',r=0.1) 42 | 43 | The default value of species is 'hsa', represents human species. 44 | The ratio r is the min threshold. The default value is 0.01. 45 | Entrez Gene ID is supported. The result will be output to a html file. 46 | 47 | 48 | Output Description 49 | ------------------ 50 | 51 | * *Summary* 52 | 53 | This part summarizes the input data. 54 | 55 | * *Details* 56 | 57 | This part list the ranked pathways and related information as shown below. 58 | 59 | ======= =========== 60 | Column Description 61 | ======= =========== 62 | Pathway Pathway name and hyperlink to modified KEGG map 63 | Genes KEGG ID of the genes in the pathway 64 | pCount Total number of genes in the pathway 65 | Count The number of recognized genes from user input 66 | Ratio The percentage of lists that containing genes in the pathway 67 | Pvalue The combined p valude from Fisher's Method 68 | EASE EASE score defined by DAVID, from merged gene list 69 | FET P value of the Fisher Exact Test, from merged gene list 70 | Samples The number of genes in the pathway in each list 71 | ======= =========== 72 | 73 | 74 | Test data 75 | --------- 76 | 77 | See the gene list files and genelists.txt file in data/. This is just toy data. 78 | 79 | 80 | Contact 81 | ------- 82 | 83 | Author: Guipeng Li 84 | 85 | Email: guipeng.lee@gmail.com 86 | 87 | Keywords: detection,pathway,enrichment,share,multiple gene lists 88 | Platform: UNKNOWN 89 | -------------------------------------------------------------------------------- /sharepathway.egg-info/SOURCES.txt: -------------------------------------------------------------------------------- 1 | CHANGES.txt 2 | LICENSE.txt 3 | MANIFEST.in 4 | README.rst 5 | setup.py 6 | sharepathway/__init__.py 7 | sharepathway/correct_pvalues.py 8 | sharepathway/enrichment.py 9 | sharepathway/geneIDconv.py 10 | sharepathway/genes2mat.py 11 | sharepathway/linkpath2mat.py 12 | sharepathway/out2html.py 13 | sharepathway/parse_kegg.py 14 | sharepathway/readfiles.py 15 | sharepathway/run.py 16 | sharepathway.egg-info/PKG-INFO 17 | sharepathway.egg-info/SOURCES.txt 18 | sharepathway.egg-info/dependency_links.txt 19 | sharepathway.egg-info/requires.txt 20 | sharepathway.egg-info/top_level.txt -------------------------------------------------------------------------------- /sharepathway.egg-info/dependency_links.txt: -------------------------------------------------------------------------------- 1 | 2 | -------------------------------------------------------------------------------- /sharepathway.egg-info/requires.txt: -------------------------------------------------------------------------------- 1 | numpy >= 1.4.0 2 | scipy >= 0.9.0 3 | -------------------------------------------------------------------------------- /sharepathway.egg-info/top_level.txt: -------------------------------------------------------------------------------- 1 | sharepathway 2 | -------------------------------------------------------------------------------- /sharepathway/__init__.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python 2 | '''sharepathway 3 | ''' 4 | from .run import Run 5 | 6 | VERSION = '0.5.0' 7 | -------------------------------------------------------------------------------- /sharepathway/__init__.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/GuipengLi/SharePathway/95bed351eb9e860a765bb1d72064a56a8879f29f/sharepathway/__init__.pyc -------------------------------------------------------------------------------- /sharepathway/__pycache__/__init__.cpython-33.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/GuipengLi/SharePathway/95bed351eb9e860a765bb1d72064a56a8879f29f/sharepathway/__pycache__/__init__.cpython-33.pyc -------------------------------------------------------------------------------- /sharepathway/__pycache__/enrichment.cpython-33.pyc: -------------------------------------------------------------------------------- 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-------------------------------------------------------------------------------- 1 | def correct_pvalues_for_multiple_testing(pvalues, correction_type = "Benjamini-Hochberg"): 2 | """ 3 | consistent with R - print correct_pvalues_for_multiple_testing([0.0, 0.01, 0.029, 0.03, 0.031, 0.05, 0.069, 0.07, 0.071, 0.09, 0.1]) 4 | """ 5 | from numpy import array, empty 6 | pvalues = array(pvalues) 7 | n = float(pvalues.shape[0]) 8 | new_pvalues = empty(n) 9 | if correction_type == "Bonferroni": 10 | new_pvalues = n * pvalues 11 | elif correction_type == "Bonferroni-Holm": 12 | values = [ (pvalue, i) for i, pvalue in enumerate(pvalues) ] 13 | values.sort() 14 | for rank, vals in enumerate(values): 15 | pvalue, i = vals 16 | new_pvalues[i] = (n-rank) * pvalue 17 | elif correction_type == "Benjamini-Hochberg": 18 | values = [ (pvalue, i) for i, pvalue in enumerate(pvalues) ] 19 | values.sort() 20 | values.reverse() 21 | new_values = [] 22 | for i, vals in enumerate(values): 23 | rank = n - i 24 | pvalue, index = vals 25 | new_values.append((n/rank) * pvalue) 26 | for i in range(0, int(n)-1): 27 | if new_values[i] < new_values[i+1]: 28 | new_values[i+1] = new_values[i] 29 | for i, vals in enumerate(values): 30 | pvalue, index = vals 31 | new_pvalues[index] = new_values[i] 32 | return new_pvalues 33 | -------------------------------------------------------------------------------- /sharepathway/enrichment.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | 3 | def enrichment(*args, **kwargs): 4 | ''' 5 | parse link path data into matrix 6 | Input: a gene list and link path data from KEGG rest 7 | Output: a matrix for enrichment 8 | ''' 9 | GenesMat = kwargs.get('gMat', args[0]) 10 | pathwayMat = kwargs.get('pMat', args[1]) 11 | snum = GenesMat.shape[1] 12 | pnum = pathwayMat.shape[1] 13 | enrich = np.zeros([pnum,snum]) 14 | for j in range(pnum): 15 | P = pathwayMat[:,j] 16 | # genes in pathway 17 | selectMat = GenesMat[P==1,:] 18 | # need to improve 19 | enrich[j,:] = selectMat.sum(axis=0) 20 | return enrich -------------------------------------------------------------------------------- /sharepathway/enrichment.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/GuipengLi/SharePathway/95bed351eb9e860a765bb1d72064a56a8879f29f/sharepathway/enrichment.pyc -------------------------------------------------------------------------------- /sharepathway/geneIDconv.py: -------------------------------------------------------------------------------- 1 | from .parse_kegg import Request 2 | 3 | def geneIDconv(*args, **kwargs): 4 | species = kwargs.get('species', 'hsa') #default: 'hsa' 5 | ngid = kwargs.get('NCBI-GeneID', 'ncbi-geneid') 6 | # KEGG ID conv from NCBI-GeneID to KEGG ID , though most of them are the same 7 | keggd=Request('conv',species,ngid) 8 | Kgid = {} 9 | for line in keggd: 10 | Kgid[line[0].split(':')[1]] = line[1] 11 | return Kgid -------------------------------------------------------------------------------- /sharepathway/geneIDconv.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/GuipengLi/SharePathway/95bed351eb9e860a765bb1d72064a56a8879f29f/sharepathway/geneIDconv.pyc -------------------------------------------------------------------------------- /sharepathway/genes2mat.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | def genes2mat(*args, **kwargs): 3 | ''' 4 | parse gene lists into matrix 5 | Input: N gene lists, NCBI-GeneID 6 | Output: a matrix''' 7 | genelists = kwargs.get('glists', args[0]) 8 | Genes = kwargs.get('genes', args[1]) 9 | samplesnum = kwargs.get('N', 10) 10 | 11 | genesnum = len(Genes) 12 | samplesnum = len(genelists) 13 | GenesMat = np.zeros([genesnum,samplesnum]) 14 | j = 0 15 | for gl in genelists: 16 | for g in gl: 17 | GenesMat[Genes.index(g),j] = 1 18 | j = j+1 19 | return GenesMat 20 | 21 | -------------------------------------------------------------------------------- /sharepathway/genes2mat.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/GuipengLi/SharePathway/95bed351eb9e860a765bb1d72064a56a8879f29f/sharepathway/genes2mat.pyc -------------------------------------------------------------------------------- /sharepathway/linkpath2mat.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | 3 | def linkpath2mat(*args, **kwargs): 4 | ''' 5 | parse link path data into matrix 6 | Input: a gene list and link path data from KEGG rest 7 | Output: a matrix for enrichment... 8 | ''' 9 | Genes = kwargs.get('genes', args[0]) 10 | data = kwargs.get('pathways', args[1]) 11 | genesnum = len(Genes) 12 | Pathways = [] 13 | i = 0 14 | # pathway genes count 15 | pathwaycount = [] 16 | for line in data: 17 | # ('hsa:10', 'path:hsa00983') 18 | #gene = geneIDconv(gene) 19 | gene = line[0] 20 | pathway = line[1] 21 | if pathway not in Pathways: 22 | Pathways.append(pathway) 23 | pathwaycount.append(1) 24 | else: 25 | pathwaycount[Pathways.index(pathway)] = pathwaycount[Pathways.index(pathway)]+1 26 | pathwaysnum = len(Pathways) 27 | # generate matrix 28 | pathwayMat = np.zeros([genesnum, pathwaysnum]) 29 | for line in data: 30 | gene = line[0] 31 | pathway = line[1] 32 | if gene in Genes: 33 | i = Genes.index(gene) 34 | j = Pathways.index(pathway) 35 | pathwayMat[i,j] = 1 36 | return [Pathways, pathwaycount, pathwayMat] 37 | -------------------------------------------------------------------------------- /sharepathway/linkpath2mat.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/GuipengLi/SharePathway/95bed351eb9e860a765bb1d72064a56a8879f29f/sharepathway/linkpath2mat.pyc -------------------------------------------------------------------------------- /sharepathway/out2html.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | import time 3 | from scipy import stats 4 | 5 | def out2html(*args, **kwargs): 6 | ''' 7 | parse link path data into matrix 8 | Input: a gene list and link path data from KEGG rest 9 | Output: a matrix for enrichment 10 | ''' 11 | print('Saving the result to html...') 12 | localtime = time.asctime(time.localtime(time.time())) 13 | #Genes = kwargs.get('enrich', args[0]) 14 | #Pathways = kwargs.get('GenesMat', args[1]) 15 | GenesMat = kwargs.get('GenesMat', args[0]) 16 | pathwayMat = kwargs.get('pathwayMat', args[1]) 17 | enrich = kwargs.get('enrich', args[2]) 18 | Genes = kwargs.get('Genes', args[3]) 19 | Pathways = kwargs.get('Pathways', args[4]) 20 | genelists = kwargs.get('genelists', args[5]) 21 | pathwaycount = kwargs.get('pathwaycount', args[6]) 22 | rr = kwargs.get('ratio',args[7]) 23 | outfilename = kwargs.get('output', args[8]) 24 | pwid2name = dict(kwargs.get('pwid2name', args[9])) 25 | snum = GenesMat.shape[1] 26 | pnum = pathwayMat.shape[1] 27 | gnum = GenesMat.shape[0] 28 | genelistscount = [len(gl) for gl in genelists] 29 | 30 | fs = open(outfilename+'-test.txt', 'w') 31 | outfile = open(outfilename, "w") 32 | 33 | outfile.write(""" 34 | 35 | 36 | 37 | Sharepathway Result 38 | 39 | 40 | 41 | 81 | 88 | """) 89 | #summary 90 | outfile.write(""" 91 | 92 |
93 |

Summary

94 |

95 |
    96 |
  • Species: %s
    • 97 |
  • Totol number of pathway: %d
    • 98 |
  • Number of input samples: %d
    • 99 |
  • Number of input genes per sample: %s
    • 100 |
  • Totol number of unique input genes: %d
    • 101 |
  • This file is created by sharepathway at %s
    • 102 |
103 |

104 |
105 | """ %('hsa',pnum,snum,str(genelistscount),gnum, localtime)) 106 | 107 | 108 | outfile.write(""" 109 |
110 |

Details

111 | 112 | 113 | 114 | 115 | 116 | 117 | 118 | 119 | 120 | 121 | 122 | 123 | 124 | 125 | """) 126 | counter = 1 127 | for i in range(enrich.shape[0]): 128 | ratio = (np.sum(enrich[i,:]>0)+0.0)/enrich.shape[1] 129 | if ratio > rr: 130 | samples = enrich[i,:] 131 | ratio = ratio 132 | # prepare the table 133 | pathwayid = Pathways[i] 134 | if pathwayid in pwid2name: 135 | pwname = pwid2name[pathwayid].split(' - ')[0].strip() 136 | genes = [str(g) for g,p in zip(Genes,pathwayMat[:,i]) if p] 137 | genesid = '+'.join([g.split(':')[1] for g in genes]) 138 | mapid = "http://www.kegg.jp/pathway/"+pathwayid.split(':')[1]+'+'+genesid 139 | count = len(genes) 140 | # get p-value 141 | pn = pathwaycount[i] 142 | x2value = 0 143 | j = 0 144 | for s in samples: 145 | fp = stats.fisher_exact([[s,genelistscount[j]-s],[pn,30000-pn]])[1] 146 | #if fp<0.1: 147 | # print(s,pn,genelistscount[j],fp) 148 | j = j+1 149 | x2value = x2value -2*np.log(fp) 150 | #pvalue = -np.log10(1 - stats.chi2.cdf(x2value,2*snum)+1e-10) 151 | #pvalue = 1 - stats.chi2.cdf(x2value,2*snum) 152 | pvalue = stats.chisqprob(x2value,2*snum) 153 | ease = stats.fisher_exact([[count-1,gnum-count],[pn,30000-pn]])[1] 154 | fet = stats.fisher_exact([[count,gnum-count],[pn,30000-pn]])[1] 155 | # hyperlink to mapid 156 | strsamples = ', '.join([str(int(i)) for i in samples]) 157 | outfile.write('''''' % ( 158 | mapid, pwname, genes, pn,count, ratio, pvalue, ease, fet, strsamples)) 159 | fs.write('''%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\t%s\n''' %(pwname, genes, pn,count, ratio, pvalue, ease, fet, strsamples)) 160 | counter += 1 161 | outfile.write("""
PathwayGenespCountCountRatioPvalueEASEFETSamples
%s%s%s%s%.2f%.2E%.2E%.2E%s
""") 162 | outfile.write("""
Copyright 2014-2017 by Guipeng Li. All Rights Reserved.
""") 163 | outfile.close() 164 | fs.close() 165 | return enrich 166 | -------------------------------------------------------------------------------- /sharepathway/out2html.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/GuipengLi/SharePathway/95bed351eb9e860a765bb1d72064a56a8879f29f/sharepathway/out2html.pyc -------------------------------------------------------------------------------- /sharepathway/parse_kegg.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | from itertools import chain, groupby 3 | from collections import defaultdict 4 | import pickle 5 | try: 6 | from urllib2 import urlopen,HTTPError 7 | except ImportError: 8 | from urllib.request import urlopen 9 | from urllib.error import HTTPError 10 | 11 | ''' Use NCBI-geneid as internal id ''' 12 | 13 | def Request(*args, **kwargs): 14 | """return and save the blob of data that is returned 15 | from kegg without caring to the format""" 16 | downloaded = kwargs.get('force', False) 17 | save = kwargs.get('force', True) 18 | 19 | # so you can copy paste from kegg 20 | '''URL form 21 | http://rest.kegg.jp/// 22 | 23 | = info | list | find | get | conv | link 24 | = | 25 | ''' 26 | args = list(chain.from_iterable(a.split('/') for a in args)) 27 | args = [a for a in args if a] 28 | request = 'http://rest.kegg.jp/' + "/".join(args) 29 | print(("KEGG API: " + request)) 30 | filename = "KEGG_" + "_".join(args) 31 | try: 32 | if downloaded: 33 | raise IOError() 34 | print(("loading the cached file " + filename)) 35 | with open(filename, 'rb') as f: 36 | data = pickle.load(f) 37 | except IOError: 38 | print("downloading the library,it may take some time") 39 | try: 40 | req = urlopen(request) 41 | data = req.read().decode() 42 | data = [tuple(d.split('\t')) for d in data.split('\n')][:-1] 43 | if save: 44 | with open(filename, 'wb') as f: 45 | print(("saving the file to " + filename)) 46 | pickle.dump(data, f) 47 | # clean the error stacktrace 48 | except HTTPError as e: 49 | raise e 50 | return data 51 | 52 | 53 | def Parse_KEGG(*args, **kwargs): 54 | species = kwargs.get('species', 'hsa') #default: 'hsa' 55 | data=Request('link','path',species) 56 | return data 57 | -------------------------------------------------------------------------------- /sharepathway/parse_kegg.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/GuipengLi/SharePathway/95bed351eb9e860a765bb1d72064a56a8879f29f/sharepathway/parse_kegg.pyc -------------------------------------------------------------------------------- /sharepathway/readfiles.py: -------------------------------------------------------------------------------- 1 | def readfiles(*args, **kwargs): 2 | ''' 3 | parse gene list files into genelists 4 | Input: N gene lists, NCBI-GeneID 5 | Output: list of lists (genelists)''' 6 | files = kwargs.get('files', args[0]) 7 | KGID = kwargs.get('kgid', args[1]) 8 | Genes = [] 9 | tmpset = set() 10 | genelists = [] 11 | j = 0 12 | with open(files, 'r') as fs: 13 | for f in fs: 14 | print(("Loading the file " + files)) 15 | f = f.strip() 16 | genelists.append([]) 17 | with open(f,'r') as genelist: 18 | for gene in genelist: 19 | gene = gene.strip() 20 | if gene in KGID: 21 | gene = KGID[gene] 22 | #gene = geneIDconv(gene) 23 | genelists[j].append(gene) 24 | if gene not in tmpset: 25 | Genes.append(gene) 26 | tmpset.add(gene) 27 | j = j+1 28 | genesnum = len(Genes) 29 | return [Genes, genelists] 30 | -------------------------------------------------------------------------------- /sharepathway/run.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | from itertools import chain, groupby 3 | from collections import defaultdict 4 | import pickle 5 | import numpy as np 6 | 7 | from .enrichment import enrichment 8 | from .geneIDconv import geneIDconv 9 | from .genes2mat import genes2mat 10 | from .linkpath2mat import linkpath2mat 11 | from .out2html import out2html 12 | from .parse_kegg import Request 13 | from .readfiles import readfiles 14 | 15 | def Run(*args, **kwargs): 16 | '''KEGG pathway enrichment analysis with multiple gene lists 17 | Keyword arguments: 18 | fi -- input file containing gene list file names 19 | fo -- output html file name 20 | species -- KEGG organism code (default:hsa) , see http://rest.kegg.jp/list/organism 21 | r -- ratio, only output the pathway with ratio>r (default:0.01) 22 | Example: 23 | Run(fi="genelist.txt",fo="result") 24 | ''' 25 | 26 | species = kwargs.get('species', 'hsa') #default: 'hsa' 27 | filein = kwargs.get('fi') 28 | fileout = kwargs.get('fo') 29 | genelists = kwargs.get('glist') 30 | 31 | fileout = fileout+'.html' 32 | ratio = kwargs.get('r',0.01) 33 | # parse gene lists into matrix 34 | KGID = geneIDconv(species=species) 35 | Genes = set() 36 | if filein and not genelists: 37 | [Genes, genelists] = readfiles(filein,KGID) 38 | print('Read from file...') 39 | else: 40 | glists = genelists 41 | ii = 0 42 | for gl in genelists: 43 | glists[ii] = [KGID[row] for row in gl if row in KGID] 44 | Genes = Genes.union(set(glists[ii])) 45 | ii = ii+1 46 | Genes = list(Genes) 47 | 48 | print('Read from python variable...') 49 | 50 | GenesMat = genes2mat(genelists,Genes) 51 | # load KEGG data 52 | data=Request('link','path',species) 53 | pwid2name = Request('list','pathway',species) 54 | # parse KEGG into matrix 55 | [Pathways, pathwaycount, pathwayMat] = linkpath2mat(Genes, data) 56 | enrich = enrichment(GenesMat, pathwayMat) 57 | result = out2html(GenesMat, pathwayMat,enrich,Genes,Pathways,genelists,pathwaycount,ratio,fileout, pwid2name) 58 | return(result) 59 | 60 | -------------------------------------------------------------------------------- /sharepathway/run.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/GuipengLi/SharePathway/95bed351eb9e860a765bb1d72064a56a8879f29f/sharepathway/run.pyc -------------------------------------------------------------------------------- /sharepathway/test/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/GuipengLi/SharePathway/95bed351eb9e860a765bb1d72064a56a8879f29f/sharepathway/test/__init__.py --------------------------------------------------------------------------------