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A Python package for KEGG pathway enrichment analysis with multiple gene lists

Project description

SharePathway is a python package for KEGG pathway enrichment analysis with multiple gene lists.

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.

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.


This version is for both python2 and python3. The first step is to install Python. Python is available from the Python project page . The next step is install sharepathway.

Install from PyPi using pip, a package manager for Python:

$ pip install sharepathway

Or, you can download the source code at Github or at PyPi for SharePathway, and then run:

$ python install


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:

import sharepathway as sp

The default value of species is ‘hsa’, represents human species. The ratio r is the min threshold. The default value is 0.01. Entrez Gene ID is supported. The result will be output to a html file.

Output Description

  • Summary

    This part summarizes the input data.

  • Details

    This part list the ranked pathways and related information as shown below.




    Pathway name and hyperlink to modified KEGG map


    KEGG ID of the genes in the pathway


    Total number of genes in the pathway


    The number of recognized genes from user input


    The percentage of lists that containing genes in the pathway


    The combined p valude from Fisher’s Method


    EASE score defined by DAVID, from merged gene list


    P value of the Fisher Exact Test, from merged gene list


    The number of genes in the pathway in each list

Test data

See the gene list files and genelists.txt file in data/. This is just toy data.


Author: Guipeng Li


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