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

Journal: Scientific reports
Published Date: Mar 23, 2018

Abstract

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.

Authors

  • Aurelie Tomczak
    Stanford Institute for Immunity, Transplantation and Infection (ITI), Stanford University, Stanford, CA, 94305, USA.
  • Jonathan M Mortensen
    Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, CA 94305-5479, United States; Biomedical Informatics Training Program, Stanford University, Stanford, CA 94305-5479, United States.
  • Rainer Winnenburg
    Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine, Stanford University, Stanford, CA, 94305, USA.
  • Charles Liu
    Stanford Institute for Immunity, Transplantation and Infection (ITI), Stanford University, Stanford, CA, 94305, USA.
  • Dominique T Alessi
    Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine, Stanford University, Stanford, CA, 94305, USA.
  • Varsha Swamy
    Stanford Institute for Immunity, Transplantation and Infection (ITI), Stanford University, Stanford, CA, 94305, USA.
  • Francesco Vallania
    Stanford Institute for Immunity, Transplantation and Infection (ITI), Stanford University, Stanford, CA, 94305, USA.
  • Shane Lofgren
    Stanford Institute for Immunity, Transplantation and Infection (ITI), Stanford University, Stanford, CA, 94305, USA.
  • Winston Haynes
    Stanford Institute for Immunity, Transplantation and Infection (ITI), Stanford University, Stanford, CA, 94305, USA.
  • Nigam H Shah
    Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, CA, USA.
  • Mark A Musen
    Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, CA 94305-5479, United States. Electronic address: musen@stanford.edu.
  • Purvesh Khatri
    Department of Radiation Oncology, Stanford University School of Medicine , Stanford, California 94305, United States.

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