Large-scale multiple testing in genome-wide association studies via region-specific hidden Markov models
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Identifying genetic variants associated with complex human diseases is a great challenge in genome-wide association studies (GWAS). Single nucleotide polymorphisms (SNPs) arising from genetic background are often dependent. The existing methods, i.e., local index of significance (LIS) and pooled local index of significance (PLIS), were both proposed for modeling SNP dependence and assumed that the whole chromosome follows a hidden Markov model (HMM).
Nội dung trích xuất từ tài liệu:
Large-scale multiple testing in genome-wide association studies via region-specific hidden Markov models
Nội dung trích xuất từ tài liệu:
Large-scale multiple testing in genome-wide association studies via region-specific hidden Markov models
Tìm kiếm theo từ khóa liên quan:
Genome-wide association studies Single nucleotide polymorphisms Local index of significance Hidden Markov model Modeling SNP dependenceGợi ý tài liệu liên quan:
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