2020
A Fast and Accurate Method for Genome-Wide Time-to-Event Data Analysis and Its Application to UK Biobank
Bi W, Fritsche L, Mukherjee B, Kim S, Lee S. A Fast and Accurate Method for Genome-Wide Time-to-Event Data Analysis and Its Application to UK Biobank. American Journal Of Human Genetics 2020, 107: 222-233. PMID: 32589924, PMCID: PMC7413891, DOI: 10.1016/j.ajhg.2020.06.003.Peer-Reviewed Original ResearchConceptsControlled type I error ratesTime-to-event data analysisType I error rateGenetic studies of human diseasesGenome-wide significance levelTime-to-event phenotypesSaddlepoint approximationGenome-wide analysisEuropean ancestry samplesMinor allele frequencyStudy of human diseaseElectronic health recordsCox PH regression modelRegression modelsStandard Wald testProportional hazardsBinary phenotypesData analysisAncestry samplesGenetic studiesHealth recordsUK BiobankAllele frequenciesInpatient dataCox proportional hazards
2019
A Fast and Accurate Method for Genome-wide Scale Phenome-wide G × E Analysis and Its Application to UK Biobank
Bi W, Zhao Z, Dey R, Fritsche L, Mukherjee B, Lee S. A Fast and Accurate Method for Genome-wide Scale Phenome-wide G × E Analysis and Its Application to UK Biobank. American Journal Of Human Genetics 2019, 105: 1182-1192. PMID: 31735295, PMCID: PMC6904814, DOI: 10.1016/j.ajhg.2019.10.008.Peer-Reviewed Original ResearchConceptsCase-control ratioGenome-wide significance levelMeasures of environmental exposureGenome-wide analysisEuropean ancestry samplesGenetic association studiesSaddlepoint approximationCase-control imbalanceAnalysis of phenotypesGene-environment interactionsPopulation-based biobanksControlled type I error ratesAssociation studiesG x E effectsUK BiobankType I error rateGenetic variantsE analysisSPAGEComplex diseasesEnvironmental exposuresTest statisticsE studySimulation studyWald test
2015
Comparative genome-wide association studies of a depressive symptom phenotype in a repeated measures setting by race/ethnicity in the multi-ethnic study of atherosclerosis
Ware E, Mukherjee B, Sun Y, Diez-Roux A, Kardia S, Smith J. Comparative genome-wide association studies of a depressive symptom phenotype in a repeated measures setting by race/ethnicity in the multi-ethnic study of atherosclerosis. BMC Genomic Data 2015, 16: 118. PMID: 26459564, PMCID: PMC4603946, DOI: 10.1186/s12863-015-0274-0.Peer-Reviewed Original ResearchConceptsMulti-Ethnic StudyGenome-wide association studiesStudies of depressive symptomsMulti-Ethnic Study of AtherosclerosisDepressive symptomsStudy of AtherosclerosisGenome-wide suggestive levelMeasures analysisSingle-nucleotide polymorphismsMultiple ethnicitiesBaseline measurementsMeta-analysisEuropean AmericansLongitudinal measurementsGenome-wide analysisLongitudinal frameworkSuggestive levelAssociation studiesMethodsThis studyEthnicityGenetic predictorsP-valueMood disordersHealthNovel variants