Covariate Adaptive Family-wise Error Rate Control for Genome-Wide Association Studies
نویسندگان
چکیده
منابع مشابه
Covariate-modulated local false discovery rate for genome-wide association studies
MOTIVATION Genome-wide association studies (GWAS) have largely failed to identify most of the genetic basis of highly heritable diseases and complex traits. Recent work has suggested this could be because many genetic variants, each with individually small effects, compose their genetic architecture, limiting the power of GWAS, given currently obtainable sample sizes. In this scenario, Bonferro...
متن کاملA Nonparametric Approach in Covariate - Modulated Local False Discovery Rate for Genome - Wide Association Studies
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Quality control for genome-wide association studies.
This chapter is a comprehensive review of quality control (QC) methods for SNP-based genotyping panels used in genome-wide association studies. These include QC on individuals for missingness, gender checks, duplicates and cryptic relatedness, population outliers, heterozygosity and inbreeding, and QC on SNPs for missingness, minor allele frequency and Hardy-Weinberg equilibrium. The emphasis i...
متن کاملFamily-based genome-wide association studies.
In the last 2 years, the effort to identify genes affecting common diseases and complex traits has been accelerated through the use of genome-wide association studies (GWAS). The availability of existing large collections of linkage data paved the way for the use of family-based GWAS. Although most published GWAS used population-based designs, family-based designs have played an important role,...
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in this study, effect of two genotype imputation strategies, relatedness between reference panel and test populations and minor allele frequency on imputation error rate were examined with using a stochastic simulated population. reference panel and test populations were composed of 1,000 and 500 individuals, respectively. individuals in the reference panel were genotyped with using a high and ...
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ژورنال
عنوان ژورنال: Biometrika
سال: 2020
ISSN: 0006-3444,1464-3510
DOI: 10.1093/biomet/asaa098