Featured Publications
Characterizing Spatiotemporal Transcriptome of the Human Brain Via Low-Rank Tensor Decomposition
Liu T, Yuan M, Zhao H. Characterizing Spatiotemporal Transcriptome of the Human Brain Via Low-Rank Tensor Decomposition. Statistics In Biosciences 2022, 14: 485-513. DOI: 10.1007/s12561-021-09331-5.Peer-Reviewed Original ResearchLow-rank tensor decompositionTensor decompositionPower iterationClassical principal component analysisStatistical performanceNumerical experimentsTensor unfoldingStatistical methodsGene expression dataEfficient algorithmData matrixExpression dataTensor principal componentsBrain expression dataPrincipal component analysisIterationDecompositionSpatiotemporal transcriptomeImplicit assumptionAlgorithmDynamicsTrajectoriesGuaranteesAssumptionSpatial patternsNonparametric Functional Graphical Modeling Through Functional Additive Regression Operator
Lee K, Li L, Li B, Zhao H. Nonparametric Functional Graphical Modeling Through Functional Additive Regression Operator. Journal Of The American Statistical Association 2022, 118: 1718-1732. DOI: 10.1080/01621459.2021.2006667.Peer-Reviewed Original ResearchRegression operatorMultivariate random functionsGraphical modelsOne-dimensional kernelCurse of dimensionalityRandom variablesStatistical objectsRandom functionExisting graphical modelsError boundsEstimation consistencyLarge-scale networksDistributional assumptionsGaussian distributionNonparametric approachNonlinear relationOperatorsGraphical modelingOperator levelNeighborhood selectionExponential rateSupplementary materialElectroencephalography datasetAssumptionDifferent nodesA fast and robust Bayesian nonparametric method for prediction of complex traits using summary statistics
Zhou G, Zhao H. A fast and robust Bayesian nonparametric method for prediction of complex traits using summary statistics. PLOS Genetics 2021, 17: e1009697. PMID: 34310601, PMCID: PMC8341714, DOI: 10.1371/journal.pgen.1009697.Peer-Reviewed Original ResearchConceptsBayesian nonparametric methodParameter tuningNonparametric methodsExternal reference panelSummary statisticsComputational resourcesParallel algorithmBlock structureExplicit assumptionsExisting methodsStatisticsSeparate validation dataAccurate risk prediction modelsAssumptionPrediction modelPredictionAlgorithm
2022
Mendelian randomization for causal inference accounting for pleiotropy and sample structure using genome-wide summary statistics
Hu X, Zhao J, Lin Z, Wang Y, Peng H, Zhao H, Wan X, Yang C. Mendelian randomization for causal inference accounting for pleiotropy and sample structure using genome-wide summary statistics. Proceedings Of The National Academy Of Sciences Of The United States Of America 2022, 119: e2106858119. PMID: 35787050, PMCID: PMC9282238, DOI: 10.1073/pnas.2106858119.Peer-Reviewed Original Research