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 sampleAncestralAssociationGeneticsSequenceCopy-number variants differ in frequency across genetic ancestry groups
Schultz L, Knighton A, Huguet G, Saci Z, Jean-Louis M, Mollon J, Knowles E, Glahn D, Jacquemont S, Almasy L. Copy-number variants differ in frequency across genetic ancestry groups. Human Genetics And Genomics Advances 2024, 5: 100340. PMID: 39138864, PMCID: PMC11401192, DOI: 10.1016/j.xhgg.2024.100340.Peer-Reviewed Original ResearchCopy number variantsAncestry groupsDeleterious copy number variantsRecurrent copy number variantsNon-European ancestry groupsUK BiobankGenetic ancestry groupsGenetic ancestryEuropean ancestry groupsReplication cohortFamily cohortProbe associationsAncestryCopyVariantsHealth outcomesCognitive phenotypesCommunity populationAutism spectrum disorderPhenotypeCohort
This site is protected by hCaptcha and its Privacy Policy and Terms of Service apply