Pathway size matters: the influence of pathway granularity on over-representation (enrichment analysis) statistics.

ABSTRACT:

Background

Enrichment or over-representation analysis is a common method used in bioinformatics studies of transcriptomics, metabolomics, and microbiome datasets. The key idea behind enrichment analysis is: given a set of significantly expressed genes (or metabolites), use that set to infer a smaller set of perturbed biological pathways or processes, in which those genes (or metabolites) play a role. Enrichment computations rely on collections of defined biological pathways and/or processes, which are usually drawn from pathway databases. Although practitioners of enrichment analysis take great care to employ statistical corrections (e.g., for multiple testing), they appear unaware that enrichment results are quite sensitive to the pathway definitions that the calculation uses.

SUBMITTER: Karp PD 

PROVIDER: S-EPMC7967953 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature