Article

Selecting Covariates for Genome-Wide Association Studies

2023-02-07

Abstract excerpt

The choice of which covariates to include in a Genome-Wide Association Study (GWAS) is important since it affects the ability to detect true association signal of variants, to correct for confounders and avoid false positives, and the running time of the analysis. Commonly used covariates include age, sex, genotyping batches, genotyping array type, as well as an arbitrary number of Principal Components (PCs) used...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 6ec005e4-b118-5087-9aa8-576486eea352
DOI: 10.1101/2023.02.07.527425

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Selecting Covariates for Genome-Wide Association StudiesDOI 10.1101/2023.02.07.527425Read

Adjusting for population stratification in polygenic risk score analyses: a guide for model specifications in the UK Biobank.Semantic proximity Read

A guide to performing Polygenic Risk Score analysesSemantic proximity Read

A simple approach for multiple observations improves power to detect genetic effects and genomic prediction accuracy.Semantic proximity Read

Expanded utility of the R package qgg with applications within genomic medicineSemantic proximity Read

Phenome-wide heritability analysis of the UK Biobank.Semantic proximity Read

A tutorial on conducting genome-wide association studies: Quality control and statistical analysis.Semantic proximity Read

Phenome-wide Heritability Analysis of the UK BiobankSemantic proximity Read

Tutorial: a guide to performing polygenic risk score analyses.Semantic proximity Read

Calculating Polygenic Risk Scores (PRS) in UK Biobank: A Practical Guide for EpidemiologistsSemantic proximity Read

Computationally efficient, exact, covariate-adjusted genetic principal component analysis by leveraging individual marker summary statistics from large biobanks.Semantic proximity Read

Efficient polygenic risk scores for biobank scale data by exploiting phenotypes from inferred relatives.Semantic proximity Read

Performing post-genome-wide association study analysis: overview, challenges and recommendationsSemantic proximity Read