Abstract
BackgroundThe Gene Ontology (GO) is one of the most widely used resources in molecular and cellular biology, largely through the use of “enrichment analysis.” To facilitate informed use of GO, we present GOtrack (https://gotrack.msl.ubc.ca), which provides access to historical records and trends in the GO and GO annotations.FindingsGOtrack gives users access to gene- and term-level information on annotations for nine model organisms as well as an interactive tool that measures the stability of enrichment results over time for user-provided “hit lists” of genes. To document the effects of GO evolution on enrichment, we analyzed more than 2,500 published hit lists of human genes (most older than 9 years ); 53% of hit lists were considered to yield significantly stable enrichment results.ConclusionsBecause stability is far from assured for any individual hit list, GOtrack can lead to more informed and cautious application of GO to genomics research.
Highlights
The Gene Ontology (GO) is one of the most widely used resources in molecular and cellular biology, largely through the use of “enrichment analysis”
To facilitate informed use of GO, we present GOtrack, which provides access to historical records and trends in the Gene Ontology and GO annotations (GOA)
19 editions of GOA yielding a grand total of 206,894,446 GO annotations
Summary
The Gene Ontology (GO) is one of the most widely used resources in molecular and cellular biology, largely through the use of “enrichment analysis”. To facilitate informed use of GO, we present GOtrack (https://gotrack.msl.ubc.ca), which provides access to historical records and trends in the Gene Ontology and GO annotations (GOA). In a typical simple setting, researchers contrast a genome-wide feature (e.g., gene expression levels or genetic association) in two experimental conditions and generate a list of genes, either ranked across the whole genome, or in the form of a “hit list” of selected candidates. Another way such lists can be generated is by clustering, such 61. To help extract biological meaning from those rankings and hit lists, 7 it is standard practice to use GO annotations in an “enrichment” framework. 9
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