PreprintCited by 0Bioinformatics and Genomic Networksscientometrics and bibliometrics researchBiomedical Text Mining and Ontologies

Meta-Research: understudied genes are lost in a leaky pipeline between genome-wide assays and reporting of results

Open access
Richardson, Reese AK, Navarro, Heliodoro Tejedor, Nunes Amaral, Luis A, Stoeger, Thomas·2024·eLife

Preprint — published as 10.7554/elife.93429.3 · Paper page

Abstract

Abstract Present-day publications on human genes primarily feature genes that already appeared in many publications prior to completion of the Human Genome Project in 2003. These patterns persist despite the subsequent adoption of high-throughput technologies, which routinely identify novel genes associated with biological processes and disease. Although several hypotheses for bias in the selection of genes as research targets have been proposed, their explanatory powers have not yet been compared. Our analysis suggests that understudied genes are systematically abandoned in favor of better-studied genes between the completion of -omics experiments and the reporting of results. Understudied genes remain abandoned by studies that cite these -omics experiments. Conversely, we find that publications on understudied genes may even accrue a greater number of citations. Among 45 biological and experimental factors previously proposed to affect which genes are being studied, we find that 33 are significantly associated with the choice of hit genes presented in titles and abstracts of - omics studies. To promote the investigation of understudied genes we condense our insights into a tool, find my understudied genes (FMUG), that allows scientists to engage with potential bias during the selection of hits. We demonstrate the utility of FMUG through the identification of genes that remain understudied in vertebrate aging. FMUG is developed in Flutter and is available for download at fmug.amaral.northwestern.edu as a MacOS/Windows app.

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Authors
Richardson, R. A., Navarro, H. T., Nunes Amaral, L. A., & Stoeger, T.
Affiliations
  • Northwestern University (US)
  • Department of Chemical and Biological Engineering, Northwestern University
Venue
eLife
Published
2024-03-12
ISSN
2050-084X (ISSN-L)
OpenAlex
W4392705522
Cited by
0
References
10
Type
posted content
Language
en
Open access
Locations
eLife (acceptedVersion, cc-by)
Funders
  • National Institute on Aging (R00AG068544, K99AG068544)
  • National Institute of Allergy and Infectious Diseases (U19AI135964)
  • National Institute of General Medical Sciences (T32GM008449)
  • National Science Foundation (1956338)
  • Simons Foundation (DMS-1764421)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › scientometrics and bibliometrics research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Biomedical Text Mining and Ontologies
Keywords
omics data, publication bias, citation impact, meta-research

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