Tao Wang, PhD
Assistant Professor Adjunct of BiostatisticsCards
About
Research
Publications
2026
Bridging unpaired single-cell multimodal data for integrative analyses with SuperMap
Deng C, Ma X, Lu H, Zhao H, Ming J, Wang T. Bridging unpaired single-cell multimodal data for integrative analyses with SuperMap. Proceedings Of The National Academy Of Sciences Of The United States Of America 2026, 123: e2505182123. PMID: 41650244, PMCID: PMC12890892, DOI: 10.1073/pnas.2505182123.Peer-Reviewed Original Research
2025
PRIME: a database for 16S rRNA microbiome data with phenotypic reference and comprehensive metadata
Zhang Z, Zhao H, Wang T. PRIME: a database for 16S rRNA microbiome data with phenotypic reference and comprehensive metadata. Nucleic Acids Research 2025, 54: d255-d263. PMID: 41171140, PMCID: PMC12807763, DOI: 10.1093/nar/gkaf1057.Peer-Reviewed Original ResearchConceptsTaxonomic abundance profilesAmplicon sequencing dataSequence dataRead countsTaxonomic levelsManual curationMicrobiome dataSequencing protocolPhenotypic referenceRelative abundanceBody sitesProgrammatic accessReference databasePhenotypic categoriesR packageAbundance profilesWeb interfaceCross-study analysisAbundanceComprehensive metadataMicrobiomeSequenceSitesDisease statusData Thinning for Poisson Factor Models and its Applications
Wang Z, Xu P, Zhao H, Wang T. Data Thinning for Poisson Factor Models and its Applications. Journal Of The American Statistical Association 2025, ahead-of-print: 1-14. DOI: 10.1080/01621459.2025.2546577.Peer-Reviewed Original ResearchPoisson factor modelSelection consistencyCovariance penaltyDimension reductionData-driven criteriaFactor modelSimulation exampleTraining errorData structuresCounting datasetsPoisson distributionSupplementary materialsDiverse domainsEfficient algorithmData applicationsInformation criterionData splittingPoissonValidation errorDataStandard descriptionICDTAd hoc criteriaData thinningSample sizeInterVelo: a mutually enhancing model for estimating pseudotime and RNA velocity in multi-omic single-cell data
Wang Y, Lin Z, Wang T. InterVelo: a mutually enhancing model for estimating pseudotime and RNA velocity in multi-omic single-cell data. Bioinformatics 2025, 41: btaf500. PMID: 40929041, PMCID: PMC12552101, DOI: 10.1093/bioinformatics/btaf500.Peer-Reviewed Original ResearchConceptsRNA velocitySingle-cell dataIntegration of multi-omics dataConstant transcription rateMulti-omics dataTranscriptional dynamicsComplex biological systemsRNA velocity estimatesDriver genesTranscription rateEnrichment analysisRNAGenesCellular timePseudotimeBiological realityBiological systemsFlexible architectureDeep learning frameworkLearning frameworkProbabilistic exponential family inverse regression and its applications
Pang D, Zhu R, Zhao H, Wang T. Probabilistic exponential family inverse regression and its applications. Biometrics 2025, 81: ujaf065. PMID: 40407023, DOI: 10.1093/biomtc/ujaf065.Peer-Reviewed Original ResearchConceptsExponential familyDouble exponential familyHigh-dimensional regressionLow-dimensional reductionHierarchical likelihoodData exampleInverse regressionDiscrete predictorsSimulation studyDiscrete dataHigh-dimensional dataParallelizable algorithmContinuous predictorsPresence–absence recordsDimension reductionResponse variablesAccumulation of high dimensional dataHigh-throughput sequencing technologyFactor model frameworkLatent factorsRecords of speciesSequence readsSingle-cell studiesSequencing technologiesCommunity ecologyCRAmed: a conditional randomization test for high-dimensional mediation analysis in sparse microbiome data
Liu T, Xu X, Wang T, Xu P. CRAmed: a conditional randomization test for high-dimensional mediation analysis in sparse microbiome data. Bioinformatics 2025, 41: btaf038. PMID: 39880365, PMCID: PMC11821267, DOI: 10.1093/bioinformatics/btaf038.Peer-Reviewed Original ResearchConceptsMicrobiome dataHuman complex traitsHost healthComplex traitsMicrobiome studiesPresence-absenceMicrobiomeHigh-dimensional mediation analysisStatistical frameworkSuperior performanceConditional randomization testMediation analysis methodsNatural indirect effectMicrobesMediation analysisF1 scoreLevel of robustnessHuman healthAbundanceTraitsData applicationsHostIndirect effects
2024
mbDriver: identifying driver microbes in microbial communities based on time-series microbiome data
Tan X, Xue F, Zhang C, Wang T. mbDriver: identifying driver microbes in microbial communities based on time-series microbiome data. Briefings In Bioinformatics 2024, 25: bbae580. PMID: 39526854, PMCID: PMC11551971, DOI: 10.1093/bib/bbae580.Peer-Reviewed Original ResearchmbDecoda: a debiased approach to compositional data analysis for microbiome surveys
Zong Y, Zhao H, Wang T. mbDecoda: a debiased approach to compositional data analysis for microbiome surveys. Briefings In Bioinformatics 2024, 25: bbae205. PMID: 38701410, PMCID: PMC11066923, DOI: 10.1093/bib/bbae205.Peer-Reviewed Original ResearchConceptsComposition of microbiomesCompositional biasMicrobiome datasetsMicrobiome studiesProbiotic microbesMicrobiome surveysMicrobiome compositionMicrobial loadMicrobiomeMaximum likelihood estimationAbundance analysisAbundance levelsAbsolute abundanceAbundance dataAbundanceClinical phenotypeFeature tableLikelihood estimation of model parametersEnvironmental factorsMaximum likelihood estimation of model parametersEstimation of model parametersMicrobesState-of-the-art methodsOver-dispersionState-of-the-art
2023
Data-driven slicing for dimension reduction in regressions: A likelihood-ratio approach
Xu P, Wang T, Zhu L. Data-driven slicing for dimension reduction in regressions: A likelihood-ratio approach. Science China Mathematics 2023, 67: 647-664. DOI: 10.1007/s11425-022-2088-x.Peer-Reviewed Original ResearchLikelihood ratio criterionDimension reductionLikelihood ratio approachAsymptotic propertiesCentral subspaceSlicing schemeInverse regressionConcrete compressive strengthSimulation studyLog-likelihood ratio criterionOptimal propertiesCompressive strengthData-driven schemeRegression-based methodsAd hocLikelihood ratioDimensionsEstimationSchemeSubspaceDiscretizationFactor Augmented Inverse Regression and its Application to Microbiome Data Analysis
Pang D, Zhao H, Wang T. Factor Augmented Inverse Regression and its Application to Microbiome Data Analysis. Journal Of The American Statistical Association 2023, 119: 1957-1967. DOI: 10.1080/01621459.2023.2231577.Peer-Reviewed Original ResearchInverse regressionCount vectorsLow-dimensional summariesAsymptotic propertiesVariational expectation-maximization algorithmExpectation-maximization algorithmGroup lassoVariational approximationApproximate inferenceSupplementary materialsCount dataModel selectionInformation criterionAbundance of featuresVectorPrediction of host phenotypeOverdispersionLatent factorsApproximation
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