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Interpretation of biological experiments changes with evolution of the Gene Ontology and its annotations.

Aurelie TomczakJonathan M MortensenRainer WinnenburgCharles LiuDominique T AlessiVarsha SwamyFrancesco VallaniaShane LofgrenWinston A HaynesNigam Haresh ShahMark A MusenPurvesh Khatri
Published in: Scientific reports (2018)
Gene Ontology (GO) enrichment analysis is ubiquitously used for interpreting high throughput molecular data and generating hypotheses about underlying biological phenomena of experiments. However, the two building blocks of this analysis - the ontology and the annotations - evolve rapidly. We used gene signatures derived from 104 disease analyses to systematically evaluate how enrichment analysis results were affected by evolution of the GO over a decade. We found low consistency between enrichment analyses results obtained with early and more recent GO versions. Furthermore, there continues to be a strong annotation bias in the GO annotations where 58% of the annotations are for 16% of the human genes. Our analysis suggests that GO evolution may have affected the interpretation and possibly reproducibility of experiments over time. Hence, researchers must exercise caution when interpreting GO enrichment analyses and should reexamine previous analyses with the most recent GO version.
Keyphrases
  • genome wide
  • high throughput
  • copy number
  • gene expression
  • endothelial cells
  • physical activity
  • dna methylation
  • transcription factor
  • deep learning
  • genome wide analysis
  • data analysis
  • resistance training