Variance component model to account for sample structure in genome-wide association studies
نویسندگان
چکیده
منابع مشابه
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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Approaches based on linear mixed models (LMMs) have recently gained popularity for modelling population substructure and relatedness in genome-wide association studies. In the last few years, a bewildering variety of different LMM methods/software packages have been developed, but it is not always clear how (or indeed whether) any newly-proposed method differs from previously-proposed implement...
متن کاملGenome-wide Association Studies
Progress in probabilistic generative models has accelerated, developing richer models with neural architectures, implicit densities, and with scalable algorithms for their Bayesian inference. However, there has been limited progress in models that capture causal relationships, for example, how individual genetic factors cause major human diseases. In this work, we focus on two challenges in par...
متن کاملGenome-wide Association Studies
Progress in probabilistic generative models has accelerated, developing richer models with neural architectures, implicit densities, and with scalable algorithms for their Bayesian inference. However, there has been limited progress in models that capture causal relationships, for example, how individual genetic factors cause major human diseases. In this work, we focus on two challenges in par...
متن کاملGenome-wide association studies.
Genome-wide association (GWA) studies are best understood as an extension of candidate gene association studies, scaled up to cover hundreds of thousands of markers across the genome in samples usually of several thousand cases and controls. The GWA approach allows the detection of much smaller effect sizes than with previous linkage-based genome-wide studies. However, this sensitivity makes th...
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ژورنال
عنوان ژورنال: Nature Genetics
سال: 2010
ISSN: 1061-4036,1546-1718
DOI: 10.1038/ng.548