dvklopfenstein / enrichmentanalysis

Generic enrichment analysis

Enrichment Analysis

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.