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Centralized scientific communities are less likely to generate replicable results

Concerns have been expressed about the robustness of experimental findings in several areas of science, but these matters have not been evaluated at scale. Here we identify a large sample of published drug-gene interaction claims curated in the Comparative Toxicogenomics Database (for example, benzo...

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Autores principales: Danchev, Valentin, Rzhetsky, Andrey, Evans, James A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6606034/
https://www.ncbi.nlm.nih.gov/pubmed/31264964
http://dx.doi.org/10.7554/eLife.43094
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author Danchev, Valentin
Rzhetsky, Andrey
Evans, James A
author_facet Danchev, Valentin
Rzhetsky, Andrey
Evans, James A
author_sort Danchev, Valentin
collection PubMed
description Concerns have been expressed about the robustness of experimental findings in several areas of science, but these matters have not been evaluated at scale. Here we identify a large sample of published drug-gene interaction claims curated in the Comparative Toxicogenomics Database (for example, benzo(a)pyrene decreases expression of SLC22A3) and evaluate these claims by connecting them with high-throughput experiments from the LINCS L1000 program. Our sample included 60,159 supporting findings and 4253 opposing findings about 51,292 drug-gene interaction claims in 3363 scientific articles. We show that claims reported in a single paper replicate 19.0% (95% confidence interval [CI], 16.9–21.2%) more frequently than expected, while claims reported in multiple papers replicate 45.5% (95% CI, 21.8–74.2%) more frequently than expected. We also analyze the subsample of interactions with two or more published findings (2493 claims; 6272 supporting findings; 339 opposing findings; 1282 research articles), and show that centralized scientific communities, which use similar methods and involve shared authors who contribute to many articles, propagate less replicable claims than decentralized communities, which use more diverse methods and contain more independent teams. Our findings suggest how policies that foster decentralized collaboration will increase the robustness of scientific findings in biomedical research.
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spelling pubmed-66060342019-07-03 Centralized scientific communities are less likely to generate replicable results Danchev, Valentin Rzhetsky, Andrey Evans, James A eLife Computational and Systems Biology Concerns have been expressed about the robustness of experimental findings in several areas of science, but these matters have not been evaluated at scale. Here we identify a large sample of published drug-gene interaction claims curated in the Comparative Toxicogenomics Database (for example, benzo(a)pyrene decreases expression of SLC22A3) and evaluate these claims by connecting them with high-throughput experiments from the LINCS L1000 program. Our sample included 60,159 supporting findings and 4253 opposing findings about 51,292 drug-gene interaction claims in 3363 scientific articles. We show that claims reported in a single paper replicate 19.0% (95% confidence interval [CI], 16.9–21.2%) more frequently than expected, while claims reported in multiple papers replicate 45.5% (95% CI, 21.8–74.2%) more frequently than expected. We also analyze the subsample of interactions with two or more published findings (2493 claims; 6272 supporting findings; 339 opposing findings; 1282 research articles), and show that centralized scientific communities, which use similar methods and involve shared authors who contribute to many articles, propagate less replicable claims than decentralized communities, which use more diverse methods and contain more independent teams. Our findings suggest how policies that foster decentralized collaboration will increase the robustness of scientific findings in biomedical research. eLife Sciences Publications, Ltd 2019-07-02 /pmc/articles/PMC6606034/ /pubmed/31264964 http://dx.doi.org/10.7554/eLife.43094 Text en © 2019, Danchev et al http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Computational and Systems Biology
Danchev, Valentin
Rzhetsky, Andrey
Evans, James A
Centralized scientific communities are less likely to generate replicable results
title Centralized scientific communities are less likely to generate replicable results
title_full Centralized scientific communities are less likely to generate replicable results
title_fullStr Centralized scientific communities are less likely to generate replicable results
title_full_unstemmed Centralized scientific communities are less likely to generate replicable results
title_short Centralized scientific communities are less likely to generate replicable results
title_sort centralized scientific communities are less likely to generate replicable results
topic Computational and Systems Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6606034/
https://www.ncbi.nlm.nih.gov/pubmed/31264964
http://dx.doi.org/10.7554/eLife.43094
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