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Enrichment Analysis

PyPI version

Do enrichment analysis on anything if you provide:

  • IDs of the population
  • IDs of the study set
  • Associations between the IDs and the terms of interest

Example data

The enrichment analysis steps performed by this repo's code

  1. Generate pvalues using Fishers exact test
  2. Do multipletest correction with any of SciPy's statsmodel functions:
multicorrect Description
sm_bonferroni bonferroni one-step correction
sm_sidak sidak one-step correction
sm_holm-sidak holm-sidak step-down method using Sidak adjustments
sm_holm holm step-down method using Bonferroni adjustments
simes-hochberg simes-hochberg step-up method (independent)
hommel hommel closed method based on Simes tests (non-negative)
fdr_bh fdr correction with Benjamini/Hochberg (non-negative)
fdr_by fdr correction with Benjamini/Yekutieli (negative)
fdr_tsbh two stage fdr correction (non-negative)
fdr_tsbky two stage fdr correction (non-negative)

To Cite

This code is a generalized version of selected code from the GOATOOLS repository, which is used to run gene ontology enrichment analysis.

Citation

Please cite the following research paper if you use this repo in your research:

Klopfenstein DV, Zhang L, Pedersen BS, ... Tang H GOATOOLS: A Python library for Gene Ontology analyses
Scientific reports | (2018) 8:10872 | DOI:10.1038/s41598-018-28948-z

Copyright (C) 2016-2019, DV Klopfenstein. All rights reserved.