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
- Generate pvalues using Fishers exact test
- 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) |
This code is a generalized version of selected code from the GOATOOLS repository, which is used to run gene ontology enrichment analysis.
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.