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Optimal design for high‐throughput screening via false discovery rate control

Tao Feng,Pallavi Basu,Wenguang Sun,H. Ku,W. Mack

Published 2017 in Statistics in Medicine

ABSTRACT

High‐throughput screening (HTS) is a large‐scale hierarchical process in which a large number of chemicals are tested in multiple stages. Conventional statistical analyses of HTS studies often suffer from high testing error rates and soaring costs in large‐scale settings. This article develops new methodologies for false discovery rate control and optimal design in HTS studies. We propose a two‐stage procedure that determines the optimal numbers of replicates at different screening stages while simultaneously controlling the false discovery rate in the confirmatory stage subject to a constraint on the total budget. The merits of the proposed methods are illustrated using both simulated and real data. We show that, at the expense of a limited budget, the proposed screening procedure effectively controls the error rate and the design leads to improved detection power.

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