Semi-supervised machine learning method for predicting homogeneous ancestry groups to assess Hardy-Weinberg equilibrium in diverse whole-genome sequencing studies
Shyr D, Dey R, Li X, Zhou H, Boerwinkle E, Buyske S, Daly M, Gibbs R, Hall I, Matise T, Reeves C, Stitziel N, Zody M, Neale B, Lin X. Semi-supervised machine learning method for predicting homogeneous ancestry groups to assess Hardy-Weinberg equilibrium in diverse whole-genome sequencing studies. American Journal Of Human Genetics 2024, 111: 2129-2138. PMID: 39270648, PMCID: PMC11480788, DOI: 10.1016/j.ajhg.2024.08.018.Peer-Reviewed Original ResearchHardy-Weinberg equilibriumWhole-genome sequencing studiesWhole-genome sequencingHomogeneous ancestryWGS studiesDownstream analysisAssociation analysisPresence of population structureAncestry groupsGenetic ancestry groupsPopulation structureSequencing studiesSelf-reported raceGenetic researchQuality variantsAncestrySubsets of samplesProgram centersVariantsIncreasing diversityHeterogeneous sampleAncestralAssociationGeneticsSequence