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.
Package details |
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Author | Yan Li [aut, cre, cph], Haochen lei [aut], Xiaoquan Wen [aut], Hongyuan Cao [aut] |
Maintainer | Yan Li <yanli_@jlu.edu.cn> |
License | GPL-3 |
Version | 1.0.1 |
Package repository | View on CRAN |
Installation |
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