Novel statistical tools for management of public databases facilitate community-wide replicability and control of false discovery.
Issues of publication bias, lack of replicability, and false discovery have long plagued the genetics community. Proper utilization of public and shared data resources presents an opportunity to ameliorate these problems. We present an approach to public database management that we term Quality Preserving Database (QPD). It enables perpetual use of the database for testing statistical hypotheses while controlling false discovery and avoiding publication bias on the one hand, and maintaining testing power on the other hand. We demonstrate it on a use case of a replication server for GWAS findings, underlining its practical utility. We argue that a shift to using QPD in managing current and future biological databases will significantly enhance the community's ability to make efficient and statistically sound use of the available data resources.
Department of Statistics and Operations Research, Tel Aviv University, Israel.
Saharon
S
Rosset
Ehud
E
Aharoni
Hani
H
Neuvirth
D016208:Databases, Factual / Q000191:economics / Q000592:standards*; D019451:Information Management / Q000191:economics / Q000379:methods* / Q000592:standards; D017150:Public Sector; D017594:Publication Bias; D011786:Quality Control; D015203:Reproducibility of Results
multiple comparisons; public databases; publication bias; quality preserving databases; replicability