ReAD: Powerful Replicability Analysis of Genome-Wide Association Studies

A robust and powerful approach is developed for replicability analysis of two Genome-wide association studies (GWASs) accounting for the linkage disequilibrium (LD) among genetic variants. The LD structure in two GWASs is captured by a four-state hidden Markov model (HMM). The unknowns involved in the HMM are estimated by an efficient expectation-maximization (EM) algorithm in combination with a non-parametric estimation of functions. By incorporating information from adjacent locations via the HMM, this approach identifies the entire clusters of genotype-phenotype associated signals, improving the power of replicability analysis while effectively controlling the false discovery rate.

Version: 1.0.1
Depends: Rcpp (≥ 1.0.10), qvalue
LinkingTo: Rcpp, RcppArmadillo
Published: 2023-06-30
DOI: 10.32614/CRAN.package.ReAD
Author: Yan Li [aut, cre, cph], Haochen lei [aut], Xiaoquan Wen [aut], Hongyuan Cao [aut]
Maintainer: Yan Li <yanli_ at jlu.edu.cn>
License: GPL-3
NeedsCompilation: yes
CRAN checks: ReAD results

Documentation:

Reference manual: ReAD.pdf

Downloads:

Package source: ReAD_1.0.1.tar.gz
Windows binaries: r-devel: ReAD_1.0.1.zip, r-release: ReAD_1.0.1.zip, r-oldrel: ReAD_1.0.1.zip
macOS binaries: r-release (arm64): ReAD_1.0.1.tgz, r-oldrel (arm64): ReAD_1.0.1.tgz, r-release (x86_64): ReAD_1.0.1.tgz, r-oldrel (x86_64): ReAD_1.0.1.tgz

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