Gene Ontology: Pitfalls, Biases, Remedies

TL;DR

This paper discusses common pitfalls, biases, and misconceptions in using the Gene Ontology, providing insights and remedies to improve data interpretation and analysis accuracy.

Contribution

It offers a comprehensive review of biases and misconceptions in GO usage and proposes best practices to mitigate these issues.

Findings

Identifies key biases affecting GO analyses

Highlights misconceptions about GO structure and annotations

Provides practical remedies for common pitfalls

Abstract

The Gene Ontology (GO) is a formidable resource but there are several considerations about it that are essential to understand the data and interpret it correctly. The GO is sufficiently simple that it can be used without deep understanding of its structure or how it is developed, which is both a strength and a weakness. In this chapter, we discuss some common misinterpretations of the ontology and the annotations. A better understanding of the pitfalls and the biases in the GO should help users make the most of this very rich resource. We also review some of the misconceptions and misleading assumptions commonly made about GO, including the effect of data incompleteness, the importance of annotation qualifiers, and the transitivity or lack thereof associated with different ontology relations. We also discuss several biases that can confound aggregate analyses such as gene enrichment analyses. For each of these pitfalls and biases, we suggest remedies and best practices.