Semiparametric covariate-modulated local false discovery rate for genome-wide association studies

DOI10.1214/17-AOAS1077zbMath1383.62301OpenAlexW2949572358MaRDI QIDQ1697396

Andrew J. Schork, Chun C. Fan, Rong W. Zablocki, Richard A. Levine, Wesley K. Thompson, Shujing Xu, Yun-Peng Wang

Publication date: 19 February 2018

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.aoas/1514430285

zbMATH Keywords

mixture of expertsgenome-wide association studyBayesian mixture modelB-spline densitiesmultiple-comparison procedures

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Protein sequences, DNA sequences (92D20) Paired and multiple comparisons; multiple testing (62J15)

Related Items (3)

Covariate Adaptive False Discovery Rate Control With Applications to Omics-Wide Multiple Testing ⋮ Covariate-adjusted multiple testing in genome-wide association studies via factorial hidden Markov models ⋮ Covariate-modulated large-scale multiple testing under dependence

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