An economic framework to prioritize confirmatory tests after a high-throughput screen.
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Abstract | How many hits from a high-throughput screen should be sent for confirmatory experiments? Analytical answers to this question are derived from statistics alone and aim to fix, for example, the false discovery rate at a predetermined tolerance. These methods, however, neglect local economic context and consequently lead to irrational experimental strategies. In contrast, the authors argue that this question is essentially economic, not statistical, and is amenable to an economic analysis that admits an optimal solution. This solution, in turn, suggests a novel tool for deciding the number of hits to confirm and the marginal cost of discovery, which meaningfully quantifies the local economic trade-off between true and false positives, yielding an economically optimal experimental strategy. Validated with retrospective simulations and prospective experiments, this strategy identified 157 additional actives that had been erroneously labeled inactive in at least one real-world screening experiment. |
Year of Publication | 2010
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Journal | J Biomol Screen
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Volume | 15
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Issue | 6
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Pages | 680-6
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Date Published | 2010 Jul
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ISSN | 1552-454X
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URL | |
DOI | 10.1177/1087057110372803
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PubMed ID | 20547534
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PubMed Central ID | PMC3069998
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Grant list | U54 HG005032-01 / HG / NHGRI NIH HHS / United States
U54-HG005032 / HG / NHGRI NIH HHS / United States
U54 HG005032 / HG / NHGRI NIH HHS / United States
R21 NS059380 / NS / NINDS NIH HHS / United States
N01 CO012400 / CO / NCI NIH HHS / United States
N01CO12400 / CA / NCI NIH HHS / United States
R21 NS059380-01 / NS / NINDS NIH HHS / United States
NS-059380 / NS / NINDS NIH HHS / United States
N01-CO-12400 / CO / NCI NIH HHS / United States
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