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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 |
| Reference manual: | ReAD.pdf |
| 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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