Bayesian Multi-Plate High-Throughput Screening of Compounds.

ABSTRACT: High-throughput screening of compounds (chemicals) is an essential part of drug discovery, involving thousands to millions of compounds, with the purpose of identifying candidate hits. Most statistical tools, including the industry standard B-score method, work on individual compound plates and do not exploit cross-plate correlation or statistical strength among plates. We present a new statistical framework for high-throughput screening of compounds based on Bayesian nonparametric modeling. The proposed approach is able to identify candidate hits from multiple plates simultaneously, sharing statistical strength among plates and providing more robust estimates of compound activity. It can flexibly accommodate arbitrary distributions of compound activities and is applicable to any plate geo

SUBMITTER: Shterev ID 

PROVIDER: S-EPMC6015058 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature