Featured Publications
Incorporating functional annotation with bilevel continuous shrinkage for polygenic risk prediction
Zhuang Y, Kim N, Fritsche L, Mukherjee B, Lee S. Incorporating functional annotation with bilevel continuous shrinkage for polygenic risk prediction. BMC Bioinformatics 2024, 25: 65. PMID: 38336614, PMCID: PMC11323637, DOI: 10.1186/s12859-024-05664-2.Peer-Reviewed Original ResearchConceptsPredictive performance of polygenic risk scoresFunctional annotationGenetic architecturePerformance of polygenic risk scoresPRS-CSAnnotation informationPolygenic risk predictionGenetic risk predictionPolygenic risk scoresFunctional annotation informationKyoto Encyclopedia of GenesRisk predictionProportion of variantsEncyclopedia of GenesGenomes (KEGGSource of annotationTrait heritabilityAnnotation groupsPathway informationQuantitative traitsKyoto EncyclopediaFunctional categoriesBackgroundGenetic variantsHeritable contributionReal world data sources
2021
Efficient mixed model approach for large-scale genome-wide association studies of ordinal categorical phenotypes
Bi W, Zhou W, Dey R, Mukherjee B, Sampson J, Lee S. Efficient mixed model approach for large-scale genome-wide association studies of ordinal categorical phenotypes. American Journal Of Human Genetics 2021, 108: 825-839. PMID: 33836139, PMCID: PMC8206161, DOI: 10.1016/j.ajhg.2021.03.019.Peer-Reviewed Original ResearchConceptsOrdinal categorical phenotypesGenome-wide association studiesCategorical phenotypesGenome-wide significant variantsRare variantsPhenotype distributionControlled type I error ratesType I error rateMixed model approachArray genotypingAssociation studiesCommon variantsQuantitative traitsSignificant variantsLogistic mixed modelsLack of analysis toolsUK BiobankLinear mixed model approachPhenotypeAssociation TestVariantsMixed modelsSignificance levelMAFTraits
2014
The Role of Environmental Heterogeneity in Meta‐Analysis of Gene–Environment Interactions With Quantitative Traits
Li S, Mukherjee B, Taylor J, Rice K, Wen X, Rice J, Stringham H, Boehnke M. The Role of Environmental Heterogeneity in Meta‐Analysis of Gene–Environment Interactions With Quantitative Traits. Genetic Epidemiology 2014, 38: 416-429. PMID: 24801060, PMCID: PMC4108593, DOI: 10.1002/gepi.21810.Peer-Reviewed Original ResearchMeSH KeywordsAlpha-Ketoglutarate-Dependent Dioxygenase FTOBiasBody Mass IndexCase-Control StudiesCholesterol, HDLCohort StudiesDiabetes Mellitus, Type 2Gene FrequencyGene-Environment InteractionGenetic Predisposition to DiseaseHumansMeta-Analysis as TopicModels, GeneticPhenotypePolymorphism, Single NucleotideProteinsQuantitative Trait, HeritableConceptsIndividual level dataMeta-analysisInverse-variance weighted meta-analysisEnvironmental heterogeneityGene-environment interaction studiesInverse-variance weighted estimatorMeta-analysis of interactionsStudy of type 2 diabetesGene-environment interactionsBody mass indexMeta-regression approachSingle nucleotide polymorphismsAdaptive weighted estimatorFTO geneType 2 diabetesMass indexMeta-regressionQuantitative traitsSummary statisticsCholesterol dataNucleotide polymorphismsLevel dataUnivariate summary statisticsData harmonizationEnvironmental covariates
2012
Principal interactions analysis for repeated measures data: application to gene–gene and gene–environment interactions
Mukherjee B, Ko Y, VanderWeele T, Roy A, Park S, Chen J. Principal interactions analysis for repeated measures data: application to gene–gene and gene–environment interactions. Statistics In Medicine 2012, 31: 2531-2551. PMID: 22415818, PMCID: PMC4046647, DOI: 10.1002/sim.5315.Peer-Reviewed Original ResearchConceptsGene-environment interactionsGene-geneLongitudinal cohort studyNormative Aging StudyHealth outcomesMain effect termsMeasured outcomesAging StudyOccupational historyEpistasis modelsEnvironmental exposuresMain effectLongitudinal natureLongitudinal dataResampling-based methodsCell meansClassification arrayQuantitative traitsInteraction analysisRobust classLeading eigenvaluesSimulation studyTime-varying effectsSubject-specificOutcomes