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Gene annotation bias impedes biomedical research.

Winston A Haynes1,2,3, Aurelie Tomczak1,2, Purvesh Khatri4,5

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Annotation bias in gene and protein resources is significant. Researchers should prioritize data-driven hypotheses over richly annotated genes to improve scientific rigor.

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Area of Science:

  • Biomedical research
  • Genomics
  • Proteomics

Background:

  • Gene and protein annotation resources exhibit substantial inequalities.
  • This bias influences the direction of biomedical research, favoring well-annotated genes.

Purpose of the Study:

  • To highlight the inequality in gene and protein annotation resources.
  • To underscore the impact of annotation bias on research focus.
  • To advocate for data-driven hypothesis generation.

Main Methods:

  • Analysis of existing gene and protein annotation datasets.
  • Evaluation of research trends based on annotation richness versus molecular data strength.

Main Results:

  • Significant disparities were identified across various gene and protein annotation platforms.
  • Biomedical researchers disproportionately focus on genes with extensive annotations, potentially overlooking those with stronger underlying molecular evidence.

Conclusions:

  • The current inequality in annotation resources creates a bias in scientific inquiry.
  • Adoption of data-driven hypothesis generation is recommended to mitigate this bias and enhance research quality.