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 |
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:
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