Gene annotation bias impedes biomedical research

Winston A Haynes; Aurelie Tomczak; Purvesh Khatri

doi:10.1038/s41598-018-19333-x

Gene annotation bias impedes biomedical research

Sci Rep. 2018 Jan 22;8(1):1362. doi: 10.1038/s41598-018-19333-x.

Authors

Winston A Haynes^{1

2

3}, Aurelie Tomczak^{1

2}, Purvesh Khatri^{4

5}

Affiliations

¹ Stanford Institute for Immunity, Transplantation, and Infection, Stanford University, Stanford, California, USA.
² Stanford Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, California, USA.
³ Biomedical Informatics Training Program, Stanford University, Stanford, California, USA.
⁴ Stanford Institute for Immunity, Transplantation, and Infection, Stanford University, Stanford, California, USA. pkhatri@stanford.edu.
⁵ Stanford Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, California, USA. pkhatri@stanford.edu.

Abstract

We found tremendous inequality across gene and protein annotation resources. We observed that this bias leads biomedical researchers to focus on richly annotated genes instead of those with the strongest molecular data. We advocate that researchers reduce these biases by pursuing data-driven hypotheses.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Bias
Biomedical Research / standards*
Computational Biology
Humans
Molecular Sequence Annotation / standards*

Abstract

Publication types

MeSH terms

Grants and funding