Featured Publications
Leveraging LD eigenvalue regression to improve the estimation of SNP heritability and confounding inflation
Song S, Jiang W, Zhang Y, Hou L, Zhao H. Leveraging LD eigenvalue regression to improve the estimation of SNP heritability and confounding inflation. American Journal Of Human Genetics 2022, 109: 802-811. PMID: 35421325, PMCID: PMC9118121, DOI: 10.1016/j.ajhg.2022.03.013.Peer-Reviewed Original ResearchConceptsLinkage disequilibrium score regressionComplex traitsSingle nucleotide polymorphismsSNP heritabilityGenome-wide association studiesDisequilibrium score regressionHigh-throughput technologiesHeritable phenotypesAssociation studiesGenetic studiesCryptic relatednessLD informationScore regressionHeritabilityGenetic contributionHeritability estimationPopulation stratificationDisease mechanismsTraitsLD matrixOnly summary statisticsUK BiobankPolygenicitySummary statisticsRelatedness
2024
LDER-GE estimates phenotypic variance component of gene–environment interactions in human complex traits accurately with GE interaction summary statistics and full LD information
Dong Z, Jiang W, Li H, DeWan A, Zhao H. LDER-GE estimates phenotypic variance component of gene–environment interactions in human complex traits accurately with GE interaction summary statistics and full LD information. Briefings In Bioinformatics 2024, 25: bbae335. PMID: 38980374, PMCID: PMC11232466, DOI: 10.1093/bib/bbae335.Peer-Reviewed Original ResearchConceptsHuman complex traitsComplex traitsGene-environment interactionsGene-environmentLinkage disequilibriumPhenotypic variance componentsPhenotypic varianceProportion of phenotypic varianceSummary statisticsEuropean ancestry subjectsUK Biobank dataAssociation summary statisticsComplete linkage disequilibriumControlled type I error ratesLD informationLD matrixVariance componentsBiobank dataType I error rateEuropean ancestrySample size increaseGenetic effectsTraitsE-I pairsSimulation study
2019
A statistical framework for cross-tissue transcriptome-wide association analysis
Hu Y, Li M, Lu Q, Weng H, Wang J, Zekavat SM, Yu Z, Li B, Gu J, Muchnik S, Shi Y, Kunkle BW, Mukherjee S, Natarajan P, Naj A, Kuzma A, Zhao Y, Crane PK, Lu H, Zhao H. A statistical framework for cross-tissue transcriptome-wide association analysis. Nature Genetics 2019, 51: 568-576. PMID: 30804563, PMCID: PMC6788740, DOI: 10.1038/s41588-019-0345-7.Peer-Reviewed Original ResearchConceptsTranscriptome-wide association analysisAssociation analysisGene-trait associationsGene expression dataGene expression levelsGenetic architectureComplex traitsMore genesGene expressionSingle tissueExpression dataAssociation resultsExpression levelsPowerful approachImputation modelHuman tissuesImputation accuracyGenotypesStatistical frameworkTissueGenesKey componentTraitsPowerful metricExpression
2017
Joint modeling of genetically correlated diseases and functional annotations increases accuracy of polygenic risk prediction
Hu Y, Lu Q, Liu W, Zhang Y, Li M, Zhao H. Joint modeling of genetically correlated diseases and functional annotations increases accuracy of polygenic risk prediction. PLOS Genetics 2017, 13: e1006836. PMID: 28598966, PMCID: PMC5482506, DOI: 10.1371/journal.pgen.1006836.Peer-Reviewed Original Research
2015
A Statistical Framework to Predict Functional Non-Coding Regions in the Human Genome Through Integrated Analysis of Annotation Data
Lu Q, Hu Y, Sun J, Cheng Y, Cheung KH, Zhao H. A Statistical Framework to Predict Functional Non-Coding Regions in the Human Genome Through Integrated Analysis of Annotation Data. Scientific Reports 2015, 5: 10576. PMID: 26015273, PMCID: PMC4444969, DOI: 10.1038/srep10576.Peer-Reviewed Original ResearchConceptsHuman genomeFunctional regionsStatistical frameworkAnnotation dataFunctional annotation dataWhole-genome annotationNon-coding regionsGenomic conservationHigh-throughput experimentsENCODE projectExperimental annotationsGenomeUnsupervised statistical learningFunctional potentialHuman geneticsStatistical learningComputational predictionsIntegrated analysisAnnotationAnnotation methodDiverse typesPowerful toolGeneticsMajor goalWeb server
2013
Guilt by rewiring: gene prioritization through network rewiring in Genome Wide Association Studies
Hou L, Chen M, Zhang CK, Cho J, Zhao H. Guilt by rewiring: gene prioritization through network rewiring in Genome Wide Association Studies. Human Molecular Genetics 2013, 23: 2780-2790. PMID: 24381306, PMCID: PMC3990172, DOI: 10.1093/hmg/ddt668.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesWide association studyDisease-associated genesGWAS signalsNetwork rewiringAssociation studiesFunctional genomic informationGene expression networksCo-expression networkDisease-associated pathwaysExpression networksGene networksGenomic informationAssociation signalsGene prioritizationDisease genesDisease locusSusceptibility lociGenesAssociation principleRewiringDisease associationsLociMillions of candidatesDisease conditions
2011
Incorporating Biological Pathways via a Markov Random Field Model in Genome-Wide Association Studies
Chen M, Cho J, Zhao H. Incorporating Biological Pathways via a Markov Random Field Model in Genome-Wide Association Studies. PLOS Genetics 2011, 7: e1001353. PMID: 21490723, PMCID: PMC3072362, DOI: 10.1371/journal.pgen.1001353.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesAssociation studiesBiological pathwaysSingle gene-based methodsMarkov random field modelGene-based methodsPrior biological knowledgeRandom field modelGWAS analysisAssociation signalsMultiple genesPathway topologyGene associationsAssociation analysisGenesBiological knowledgeField modelGenetic variantsSpecific pathwaysReal data examplePathwayStatistical inferenceConditional modes algorithmExchangeable setRegression form
2001
Multipoint Genetic Mapping with Trisomy Data
Li J, Sherman S, Lamb N, Zhao H. Multipoint Genetic Mapping with Trisomy Data. American Journal Of Human Genetics 2001, 69: 1255-1265. PMID: 11704925, PMCID: PMC1235537, DOI: 10.1086/324578.Peer-Reviewed Original ResearchConceptsExpectation-maximization algorithmMultipoint genetic mappingAmount of computationProbability distributionTrisomy dataStatistical methodsFirst approachMarkov modelSecond approachProbabilityCrossover processComputationLarge numberSetModelApproachGeneral relationshipDistributionAlgorithmNumber of markersOn Relationship Inference Using Gamete Identity by Descent Data
Zhao H, Liang F. On Relationship Inference Using Gamete Identity by Descent Data. Journal Of Computational Biology 2001, 8: 191-200. PMID: 11454305, DOI: 10.1089/106652701300312940.Peer-Reviewed Original ResearchTest of Association for Quantitative Traits in General Pedigrees: The Quantitative Pedigree Disequilibrium Test
Zhang S, Zhang K, Li J, Sun F, Zhao H. Test of Association for Quantitative Traits in General Pedigrees: The Quantitative Pedigree Disequilibrium Test. Genetic Epidemiology 2001, 21: s370-s375. PMID: 11793701, DOI: 10.1002/gepi.2001.21.s1.s370.Peer-Reviewed Original ResearchConceptsQuantitative pedigree disequilibrium testPedigree disequilibrium testQuantitative traitsTraits of interestGenetic Analysis Workshop 12Disequilibrium testGeneral pedigreesSequence dataCandidate genesGenetic markersGenetic linkageQualitative traitsLinkage disequilibriumTraitsLarge pedigreePresence of linkagePedigreeStatistical methodsFamilyNuclear familiesTests of associationGenesUnrelated nuclear familiesLinkageDisequilibriumThe Power of Transmission Disequilibrium Tests for Quantitative Traits
Li J, Wang D, Dong J, Jiang R, Zhang K, Zhang S, Zhao H, Sun F. The Power of Transmission Disequilibrium Tests for Quantitative Traits. Genetic Epidemiology 2001, 21: s632-s637. PMID: 11793752, DOI: 10.1002/gepi.2001.21.s1.s632.Peer-Reviewed Original Research
2000
Transmission/disequilibrium tests for quantitative traits.
Sun F, Flanders W, Yang Q, Zhao H. Transmission/disequilibrium tests for quantitative traits. Annals Of Human Genetics 2000, 64: 555-65. PMID: 11281218, DOI: 10.1017/s000348000000840x.Peer-Reviewed Original ResearchMultipoint Genetic Mapping with Uniparental Disomy Data
Zhao H, Li J, Robinson W. Multipoint Genetic Mapping with Uniparental Disomy Data. American Journal Of Human Genetics 2000, 67: 851-861. PMID: 10958760, PMCID: PMC1287890, DOI: 10.1086/303072.Peer-Reviewed Original ResearchLinkage disequilibrium mapping in populations of variable size using the decay of haplotype sharing and a stepwise‐mutation model
Zhang S, Zhao H. Linkage disequilibrium mapping in populations of variable size using the decay of haplotype sharing and a stepwise‐mutation model. Genetic Epidemiology 2000, 19: s99-s105. PMID: 11055377, DOI: 10.1002/1098-2272(2000)19:1+<::aid-gepi15>3.0.co;2-1.Peer-Reviewed Original Research
1999
The Interpretation of the Parameters in the Transmission/Disequilibrium Test
Zhao H. The Interpretation of the Parameters in the Transmission/Disequilibrium Test. American Journal Of Human Genetics 1999, 64: 326-328. PMID: 9915979, PMCID: PMC1377738, DOI: 10.1086/302208.Peer-Reviewed Original Research
1998
Statistical Analysis of Ordered Tetrads
Zhao H, Speed T. Statistical Analysis of Ordered Tetrads. Genetics 1998, 150: 459-472. PMID: 9725861, PMCID: PMC1460316, DOI: 10.1093/genetics/150.1.459.Peer-Reviewed Original ResearchStatistical Analysis of Half-Tetrads
Zhao H, Speed T. Statistical Analysis of Half-Tetrads. Genetics 1998, 150: 473-485. PMID: 9725862, PMCID: PMC1460320, DOI: 10.1093/genetics/150.1.473.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsChromatidsData Interpretation, StatisticalGenetic MarkersMedicago sativaModels, GeneticTrout
1997
Strategies to Identify Genes for Complex Diseases
Zhang H, Zhao H, Merikangas K. Strategies to Identify Genes for Complex Diseases. Annals Of Medicine 1997, 29: 493-498. PMID: 9562515, DOI: 10.3109/07853899709007473.Peer-Reviewed Original ResearchConceptsComplex diseasesNumerous human diseasesDisease-susceptible genesComplex human disordersHuman genomeGenetic basisHuman disordersHuman diseasesMolecular biologyGenesGenetic epidemiological studiesGenetic factorsComplex patternsDisease pathophysiologyGenomeBiologyTraitsInheritanceMultiple sclerosisBreast cancerEpidemiological studiesThe Effects of Genotyping Errors and Interference on Estimation of Genetic Distance
Goldstein D, Zhao H, Speed T. The Effects of Genotyping Errors and Interference on Estimation of Genetic Distance. Human Heredity 1997, 47: 86-100. PMID: 9097090, DOI: 10.1159/000154396.Peer-Reviewed Original Research
1996
On Genetic Map Functions
Zhao H, Speed T. On Genetic Map Functions. Genetics 1996, 142: 1369-1377. PMID: 8846913, PMCID: PMC1207133, DOI: 10.1093/genetics/142.4.1369.Peer-Reviewed Original ResearchChromosome MappingModels, Genetic