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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