gsea-api 0.3.1

Pandas API for Gene Set Enrichment Analysis in Python (GSEApy, cudaGSEA, GSEA)

Pandas API for Gene Set Enrichment Analysis in Python (GSEApy, cudaGSEA, GSEA)

• aims to provide a unified API for various GSEA implementations; uses pandas DataFrames and a hierarchy of Pythonic classes.

• file exports (exporting input for GSEA) use low-level numpy functions and are much faster than in pandas

• aims to allow researchers to easily compare different implementations of GSEA, and to integrate those in projects which require high-performance GSEA (e.g. massive screening for drug-repositioning)

• provides useful utilities for work with GMT files, or gene sets and pathways in general in Python

Example usage

from pandas import read_table
from gsea_api.expression_set import ExpressionSet
from gsea_api.gsea import GSEADesktop
from gsea_api.molecular_signatures_db import GeneSets

reactome_pathways = GeneSets.from_gmt('ReactomePathways.gmt')

gsea = GSEADesktop()

design = ['Disease', 'Disease', 'Disease', 'Control', 'Control', 'Control']
matrix = read_table('expression_data.tsv', index_col='Gene')

result = gsea.run(
    # note: contrast() is not necessary in this simple case
    ExpressionSet(matrix, design).contrast('Disease', 'Control'),
    reactome_pathways,
    metric='Signal2Noise',
    permutations=1000
)

Where expression_data.tsv is in the following format:

Gene    Patient_1   Patient_2   Patient_3   Patient_4   Patient_5   Patient_6
TACC2   0.2 0.1 0.4 0.6 0.7 2.1
TP53    2.3 0.2 2.1 2.0 0.3 0.6

Installation

To install the API use:

pip3 install gsea_api

Installing GSEA from Broad Institute

Login/register on the official GSEA website and download the gsea_3.0.jar file (or a newer version).

Please place the downloaded file in the thirdparty directory.

Installing GSEApy

To use gsea.py please install it with:

pip3 install gseapy

and link its binary to the thirdparty directory

ln -s virtual_environment_path/bin/gseapy thirdparty/gseapy

Use it with:

from gsea_api.gsea import GSEApy

gsea = GSEApy()

Installing cudaGSEA

Please clone this fork of cudaGSEA to thirdparty directory and compile the binary version (using the instructions from this repository):

git clone https://github.com/krassowski/cudaGSEA

or use the original version, which does not implement FDR calculations.

Use it with:

from gsea_api.gsea import cudaGSEA

# CPU implementation can be used with use_cpu=True
gsea = cudaGSEA(fdr='full', use_cpu=False)

Citation

Please also cite the authors of the wrapped tools that you use.

References

The initial version of this code was written for a Master thesis project at Imperial College London.