gsea-api 0.2.2

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

pip3 install gseapy

ln -s virtual_environment_path/bin/gseapy thirdparty/gseapy

from gsea_api.gsea import GSEApy

gsea = GSEApy()

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

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.