Featured Publications
Statistical Methods for Analyzing Tree-Structured Microbiome Data
Wang T, Zhao H. Statistical Methods for Analyzing Tree-Structured Microbiome Data. Frontiers In Probability And The Statistical Sciences 2021, 193-220. DOI: 10.1007/978-3-030-73351-3_8.Peer-Reviewed Original ResearchStatistical methodsOnly relative informationMicrobiome data analysisMicrobiome dataEmpirical Bayes estimationCompositional predictorsBayes estimationComputational challengesRelative informationDimension reductionAbundance matrixTaxa countsMultinomial modelMicrobiome datasetsPhylogenetic informationMicrobial taxaPhylogenetic treeSequencing technologiesOriginal ecosystemMicrobial compositionOrders of magnitudeMatrixExperimental methodsLibrary sizeZeros
2022
phyloMDA: an R package for phylogeny-aware microbiome data analysis
Liu T, Zhou C, Wang H, Zhao H, Wang T. phyloMDA: an R package for phylogeny-aware microbiome data analysis. BMC Bioinformatics 2022, 23: 213. PMID: 35668363, PMCID: PMC9169257, DOI: 10.1186/s12859-022-04744-5.Peer-Reviewed Original ResearchConceptsHost-associated microbial communitiesShared evolutionary historyMicrobiome data analysisEvolutionary historyPhylogenetic informationPhylogenetic treeMicrobial communitiesR packageSequencing technologiesAbundance dataMicrobial compositionRelative abundanceMicrobiome dataSample sitesUser-friendly toolMultivariate abundance dataAbundanceUnique opportunityUnprecedented scaleDifferent patternsTreesA Zero-Inflated Logistic Normal Multinomial Model for Extracting Microbial Compositions
Zeng Y, Pang D, Zhao H, Wang T. A Zero-Inflated Logistic Normal Multinomial Model for Extracting Microbial Compositions. Journal Of The American Statistical Association 2022, 118: 2356-2369. DOI: 10.1080/01621459.2022.2044827.Peer-Reviewed Original ResearchMaximum likelihood estimationEfficient iterative algorithmProbabilistic PCA modelsEmpirical Bayes approachApproximation estimatorVariational approximationExcessive zerosM-estimationAsymptotic normalityIterative algorithmLikelihood estimationBayes approachCount dataHigh dimensionalityRaw count dataMultinomial modelExtensive simulationsZerosSupplementary materialMicrobiome dataCompositional natureEstimationPCA modelComposition estimationApproximation
2017
Constructing Predictive Microbial Signatures at Multiple Taxonomic Levels
Wang T, Zhao H. Constructing Predictive Microbial Signatures at Multiple Taxonomic Levels. Journal Of The American Statistical Association 2017, 112: 1022-1031. DOI: 10.1080/01621459.2016.1270213.Peer-Reviewed Original ResearchBacterial taxaTaxonomic levelsMultiple taxonomic levelsDifferent taxonomic levelsDNA sequencing technologiesHuman microbiome studiesPhylogenetic treeHost phenotypeSequencing technologiesNormal human physiologyTaxaHuman microbiomeMicrobial signaturesMicrobiome studiesMicrobiome data analysisImportant groupMicrobiome dataHigh-dimensional compositional dataHuman physiologyRecent advancesMicrobesRapid advancesMajor goalMicrobiomePhenotype