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Nat Methods. 2016 Jul;13(7):577-80. doi: 10.1038/nmeth.3885. Epub 2016 May 30.

Data-driven hypothesis weighting increases detection power in genome-scale multiple testing.

Author information

1
European Molecular Biology Laboratory, Heidelberg, Germany.

Abstract

Hypothesis weighting improves the power of large-scale multiple testing. We describe independent hypothesis weighting (IHW), a method that assigns weights using covariates independent of the P-values under the null hypothesis but informative of each test's power or prior probability of the null hypothesis (http://www.bioconductor.org/packages/IHW). IHW increases power while controlling the false discovery rate and is a practical approach to discovering associations in genomics, high-throughput biology and other large data sets.

PMID:
27240256
PMCID:
PMC4930141
DOI:
10.1038/nmeth.3885
[Indexed for MEDLINE]
Free PMC Article

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