Two subtle problems with overrepresentation analysis.

ABSTRACT:

Motivation

Overrepresentation analysis (ORA) is used widely to assess the enrichment of functional categories in a gene list compared to a background list. ORA is therefore a critical method in the interpretation of 'omics data, relating gene lists to biological functions and themes. Although ORA is hugely popular, we and others have noticed two potentially undesired behaviours of some ORA tools. The first one we call the 'background problem', because it involves the software eliminating large numbers of genes from the background list if they are not annotated as belonging to any category. The second one we call the 'false discovery rate problem', because some tools underestimate the true number of parallel tests conducted.

Results

Here, we demonstrate the impact of these is

SUBMITTER: Ziemann M 

PROVIDER: S-EPMC11557902 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature