A unified framework for variance component estimation with summary statistics in genome-wide association studies

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A Unified Framework for Variance Component Estimation with Summary Statistics in Genome-wide Association Studies.

Linear mixed models (LMMs) are among the most commonly used tools for genetic association studies. However, the standard method for estimating variance components in LMMs-the restricted maximum likelihood estimation method (REML)-suffers from several important drawbacks: REML requires individual-level genotypes and phenotypes from all samples in the study, is computationally slow, and produces ...

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Bayesian Large-scale Multiple Regression with Summary Statistics from Genome-wide Association Studies.

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...

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metaCCA: summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis

MOTIVATION A dominant approach to genetic association studies is to perform univariate tests between genotype-phenotype pairs. However, analyzing related traits together increases statistical power, and certain complex associations become detectable only when several variants are tested jointly. Currently, modest sample sizes of individual cohorts, and restricted availability of individual-leve...

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ژورنال

عنوان ژورنال: The Annals of Applied Statistics

سال: 2017

ISSN: 1932-6157

DOI: 10.1214/17-aoas1052