Bayesian variable selection regression for genome-wide association studies and other large-scale problems
نویسندگان
چکیده
منابع مشابه
Bayesian Variable Selection Regression for Genome - Wide Association Studies , and Other Large - Scale Problems
We consider applying Bayesian Variable Selection Regression, or BVSR, to genome-wide association studies, and similar large-scale regression problems. Currently, typical genome-wide association studies measure hundreds of thousands, or millions, of genetic variants (SNPs), in thousands or tens of thousands of individuals, and attempt to identify regions harboring SNPs that affect some phenotype...
متن کاملSupplement to “bayesian Large-scale Multiple Regression with Summary Statistics from Genome-wide Association Studies”
A Theoretical derivation of RSS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 A.1 Proofs of propositions in main text . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 A.1.1 Proof of Proposition 2.1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 A.1.2 Proof of Proposition 2.2 . . . . . . . . . . . . . . ....
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Bayesian methods for large-scale multiple regression provide attractive approaches to the analysis of genome-wide association studies (GWAS). For example, they can estimate heritability of complex traits, allowing for both polygenic and sparse models; and by incorporating external genomic data into the priors, they can increase power and yield new biological insights. However, these methods req...
متن کاملA variable selection method for genome-wide association studies
MOTIVATION Genome-wide association studies (GWAS) involving half a million or more single nucleotide polymorphisms (SNPs) allow genetic dissection of complex diseases in a holistic manner. The common practice of analyzing one SNP at a time does not fully realize the potential of GWAS to identify multiple causal variants and to predict risk of disease. Existing methods for joint analysis of GWAS...
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Single-locus analysis is often used to analyze genome-wide association (GWA) data, but such analysis is subject to severe multiple comparisons adjustment. Multivariate logistic regression is proposed to fit a multi-locus model for case-control data. However, when the sample size is much smaller than the number of single-nucleotide polymorphisms (SNPs) or when correlation among SNPs is high, tra...
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ژورنال
عنوان ژورنال: The Annals of Applied Statistics
سال: 2011
ISSN: 1932-6157
DOI: 10.1214/11-aoas455