Centralized scientific communities are less likely to generate replicable results

Abstract

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.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jul 02, 2019
Source ID
10.7554/elife.43094

Entities

People

  • Andrey Rzhetsky
  • James A. Evans
  • Valentin Danchev

Organizations

  • Air Force Office of Scientific Research
  • Defense Advanced Research Projects Agency
  • National Science Foundation
  • Santa Fe Institute
  • Stanford University
  • University of Chicago

Tags

Fields of Study

  • Biology

Readers

  • Criminal Law
  • Regression Analysis.
  • Systems Analysis and Design

Technology Areas

  • Biotechnology