Featured Publications
SUPERGNOVA: local genetic correlation analysis reveals heterogeneous etiologic sharing of complex traits
Zhang Y, Lu Q, Ye Y, Huang K, Liu W, Wu Y, Zhong X, Li B, Yu Z, Travers BG, Werling DM, Li JJ, Zhao H. SUPERGNOVA: local genetic correlation analysis reveals heterogeneous etiologic sharing of complex traits. Genome Biology 2021, 22: 262. PMID: 34493297, PMCID: PMC8422619, DOI: 10.1186/s13059-021-02478-w.Peer-Reviewed Original ResearchConceptsLocal genetic correlationsComplex traitsGenetic correlationsGenomic regionsLocal genetic correlation analysisGenome-wide association studiesLocal genomic regionsSpecific genomic regionsGenetic correlation analysisDistinct genetic signaturesGenetic similarityGenetic signaturesAssociation studiesTraitsSample overlapStatistical frameworkSummary statisticsDisequilibriumRegionAccurate estimationSimilarity
2023
Benchmarking of local genetic correlation estimation methods using summary statistics from genome-wide association studies
Zhang C, Zhang Y, Zhang Y, Zhao H. Benchmarking of local genetic correlation estimation methods using summary statistics from genome-wide association studies. Briefings In Bioinformatics 2023, 24: bbad407. PMID: 37974509, PMCID: PMC10654488, DOI: 10.1093/bib/bbad407.Peer-Reviewed Original Research
2020
Leveraging effect size distributions to improve polygenic risk scores derived from summary statistics of genome-wide association studies
Song S, Jiang W, Hou L, Zhao H. Leveraging effect size distributions to improve polygenic risk scores derived from summary statistics of genome-wide association studies. PLOS Computational Biology 2020, 16: e1007565. PMID: 32045423, PMCID: PMC7039528, DOI: 10.1371/journal.pcbi.1007565.Peer-Reviewed Original ResearchConceptsEffect size distributionClass of methodsReal data applicationOnly summary statisticsTheoretical resultsSummary statisticsExtensive simulation resultsLD informationSimulation resultsData applicationsFirst methodImportant problemOptimal propertiesGenetic risk predictionAccurate predictionPrediction accuracyStandard PRSStatisticsPrediction method
2017
On Joint Estimation of Gaussian Graphical Models for Spatial and Temporal Data
Lin Z, Wang T, Yang C, Zhao H. On Joint Estimation of Gaussian Graphical Models for Spatial and Temporal Data. Biometrics 2017, 73: 769-779. PMID: 28099997, PMCID: PMC5515703, DOI: 10.1111/biom.12650.Peer-Reviewed Original ResearchConceptsGaussian graphical modelsTemporal dataGraphical modelsComplex data structuresJoint estimationMarkov random field modelRandom field modelParallel computingSelection consistencyData structureStatistical inferenceNeighborhood selection methodTemporal dependenciesEfficient algorithmIndividual networksMultiple groupsSpatial dataModel convergesNetwork estimationField modelSelection methodNetworkPosterior probabilitySimulation studyImproved estimation
2012
iFad: an integrative factor analysis model for drug-pathway association inference†
Ma H, Zhao H. iFad: an integrative factor analysis model for drug-pathway association inference†. Bioinformatics 2012, 28: 1911-1918. PMID: 22581178, PMCID: PMC3389771, DOI: 10.1093/bioinformatics/bts285.Peer-Reviewed Original Research
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 ResearchMeSH KeywordsAlgorithmsComputer SimulationCrohn DiseaseGenome-Wide Association StudyHumansMetabolic Networks and PathwaysModels, GeneticProbabilityConceptsGenome-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 markersComparisons of Two Methods for Haplotype Reconstruction and Haplotype Frequency Estimation from Population Data
Zhang S, Pakstis A, Kidd K, Zhao H. Comparisons of Two Methods for Haplotype Reconstruction and Haplotype Frequency Estimation from Population Data. American Journal Of Human Genetics 2001, 69: 906-912. PMID: 11536083, PMCID: PMC1226079, DOI: 10.1086/323622.Peer-Reviewed Original ResearchQuantitative Similarity-Based Association Tests Using Population Samples
Zhang S, Zhao H. Quantitative Similarity-Based Association Tests Using Population Samples. American Journal Of Human Genetics 2001, 69: 601-614. PMID: 11479834, PMCID: PMC1235489, DOI: 10.1086/323037.Peer-Reviewed Original ResearchA stochastic modeling of early HIV-1 population dynamics
Kamina A, Makuch R, Zhao H. A stochastic modeling of early HIV-1 population dynamics. Mathematical Biosciences 2001, 170: 187-198. PMID: 11292498, DOI: 10.1016/s0025-5564(00)00069-9.Peer-Reviewed Original ResearchMeSH KeywordsComputer SimulationHIV InfectionsHIV-1HumansModels, ImmunologicalMonte Carlo MethodPopulation DynamicsStochastic ProcessesViral LoadOn 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 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 ResearchTransmission/Disequilibrium Tests Using Multiple Tightly Linked Markers
Zhao H, Zhang S, Merikangas K, Trixler M, Wildenauer D, Sun F, Kidd K. Transmission/Disequilibrium Tests Using Multiple Tightly Linked Markers. American Journal Of Human Genetics 2000, 67: 936-946. PMID: 10968775, PMCID: PMC1287895, DOI: 10.1086/303073.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
On a Randomization Procedure in Linkage Analysis
Zhao H, Merikangas K, Kidd K. On a Randomization Procedure in Linkage Analysis. American Journal Of Human Genetics 1999, 65: 1449-1456. PMID: 10521312, PMCID: PMC1288298, DOI: 10.1086/302607.Peer-Reviewed Original ResearchMeSH KeywordsComputer SimulationDiabetes Mellitus, Type 1Genetic LinkageGenetic MarkersGenomeGenotypeHumansNuclear FamilyPedigreeSoftwareStatistics as TopicConceptsEfficient simulation procedureObserved test statisticSimulation-based methodTheoretical resultsTest statisticNovel simulation methodSimulation methodReal dataSimulation procedureUninformative markersTheoretical workStatistical testsPedigree structureGenomewide significance levelRandomization procedureDiabetes dataStatisticsA more powerful method to evaluate p‐values in GENEHUNTER
Zhao H, Sheffield L, Pakstis A, Knauert M, Kidd K. A more powerful method to evaluate p‐values in GENEHUNTER. Genetic Epidemiology 1999, 17: s415-s420. PMID: 10597472, DOI: 10.1002/gepi.1370170770.Peer-Reviewed Original Research