Meta-Research: COVID-19 research risks ignoring important host genes due to pre-established research patterns
- Successful Clinical Response in Pneumonia Therapy (SCRIPT) Systems Biology Center, Northwestern University, United States
- Department of Chemical and Biological Engineering, Northwestern University, United States
- Center for Genetic Medicine, Northwestern University School of Medicine, United States
- Northwestern Institute on Complex Systems (NICO), Northwestern University, United States
- Department of Molecular Biosciences, Northwestern University, United States
- Department of Physics and Astronomy, Northwestern University, United States
- Department of Medicine, Northwestern University School of Medicine, United States
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Meta-Research: COVID-19 research risks ignoring important host genes due to pre-established research patternseLife 9:e61981.https://doi.org/10.7554/eLife.61981 - Cite
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Figures
Figure 1 with 1 supplement
Most host genes implicated in COVID-19 identified by genome-wide approaches are not being investigated.
(A) Share of identified genes, which are ignored (never tagged, blue) or tagged (at least once) within the COVID-19 literature. (B) Share of tagged genes identified by a single (orange) or multiple …
Figure 1—figure supplement 1
Share of identified genes that are ignored or tagged.
Share of identified genes, which are ignored (never tagged, blue) or tagged at least once (red) within the COVID-19 literature after additionally including genes occurring in abstracts of preprints.
Figure 2 with 1 supplement
What the future holds?
Percentage of genes with indicated levels of support by the four genome-wide studies which have been tagged at least once in the COVID-19 literature. (A) Analysis restricted to the 50% of genes with …
Figure 2—figure supplement 1
Temporal trends in the diversity of COVID-19 research.
Figure 3
Availability of reagents.
(A) Drugs studied in COVID-19 related clinical trials are frequently studied within the non-COVID-19 literature. We compare non-COVID-19 publications measured for human protein-coding genes that are …
Author response image 1
Additional files
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Source code 1
Source code for curation and analysis of datasets.
- https://cdn.elifesciences.org/articles/61981/elife-61981-code1-v1.zip
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Supplementary file 1
Gene Ontology enrichment analysis for human protein-coding genes tagged in the COVID-19 literature.
- https://cdn.elifesciences.org/articles/61981/elife-61981-supp1-v1.xlsx
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Supplementary file 2
Identification of genes through multiple GWAS comparisons.
- https://cdn.elifesciences.org/articles/61981/elife-61981-supp2-v1.xlsx
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Supplementary file 3
Implicated host genes identified by multiple genome-wide studies.
- https://cdn.elifesciences.org/articles/61981/elife-61981-supp3-v1.xlsx
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Supplementary file 4
Extent of tags in COVID-19 literature compared to rate identification in genome-wide datasets.
Per-gene average share of COVID-19 literature and per-gene average identification rate in genome-wide datasets (one if identified, 0 if not identified). Shown are the ratios of this share and the rates in individual groups (100 first tagged genes, and 20% top-tagged genes) over the share and the rates of the other genes that have been tagged in the COVID-19 literature.
- https://cdn.elifesciences.org/articles/61981/elife-61981-supp4-v1.xlsx
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Supplementary file 5
Number of laboratories working on individual genes, identified within one of the four genome-wide datasets, between 2006 and 2015.
- https://cdn.elifesciences.org/articles/61981/elife-61981-supp5-v1.xlsx
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Transparent reporting form
- https://cdn.elifesciences.org/articles/61981/elife-61981-transrepform-v1.docx
