2025
Sex-biased Gene Expression Underlies Immune Dysfunction in Asthma.
Kay S, Rajeevan H, Son M, Kwah J, Ramirez M, Liu Y, Wang Z, Yan X, Nino G, Britto C, Chupp G, Gomez J. Sex-biased Gene Expression Underlies Immune Dysfunction in Asthma. American Journal Of Respiratory Cell And Molecular Biology 2025 PMID: 40587876, DOI: 10.1165/rcmb.2024-0565oc.Peer-Reviewed Original ResearchSex-biased gene expressionClinical featuresGene expressionType 2 inflammationClinical features of asthmaFeatures of asthmaAssociated with differential gene expressionExpression levelsImmune dysfunctionLocal validation cohortAdult patientsGene expression databaseValidation cohortImmune cellsClinical correlatesDifferential gene expressionGene expression differencesLymphocyte proliferationAllergic responsesAdult subjectsGene expression effectsGenetic polymorphismsImmune allergic responsesBlood samplesFemale genomesSex differences in proteomics of cardiovascular disease – Results from the Yale-CMD registry
Liu Y, Wang Z, Collins S, Testani J, Safdar B. Sex differences in proteomics of cardiovascular disease – Results from the Yale-CMD registry. IJC Heart & Vasculature 2025, 58: 101667. PMID: 40224648, PMCID: PMC11987697, DOI: 10.1016/j.ijcha.2025.101667.Peer-Reviewed Original ResearchCMD patientsUpregulation of immune pathwaysCardiovascular diseaseProximity extension assayBody mass indexRegulation of blood flowSex differencesProteomic profilingIschemic symptomsCAD patientsMass indexIncreased angiogenesisGlucose metabolic pathwaysDifferential protein expressionPatientsSex-specific pathwaysProtein expressionImmune pathwaysBlood flowBlood samplesPrecision medicineINSL3Metabolic pathwaysPathway analysisExtension assay
2024
Enhancing patient representation learning with inferred family pedigrees improves disease risk prediction
Huang X, Arora J, Erzurumluoglu A, Stanhope S, Lam D, Arora J, Erzurumluoglu A, Lam D, Khoueiry P, Jensen J, Cai J, Lawless N, Kriegl J, Ding Z, de Jong J, Zhao H, Ding Z, Wang Z, de Jong J. Enhancing patient representation learning with inferred family pedigrees improves disease risk prediction. Journal Of The American Medical Informatics Association 2024, 32: 435-446. PMID: 39723811, PMCID: PMC11833479, DOI: 10.1093/jamia/ocae297.Peer-Reviewed Original ResearchConceptsElectronic health recordsDisease risk predictionElectronic health record researchFamily health historyGenetic aspects of diseaseRisk predictionInflammatory bowel disease subtypeHealth recordsHealth historyAspects of diseaseFamily relationsHealthcare ResearchPatient's disease riskInfluence of geneticsDisease riskDiagnosis dataFamily pedigreeEnvironmental exposuresRisk factorsDisease dependencyPatient representation learningClinical profileFamilyDisease subtypesRiskMarginal interaction test for detecting interactions between genetic marker sets and environment in genome-wide studies
Shen L, Amei A, Liu B, Xu G, Liu Y, Oh E, Zhou X, Wang Z. Marginal interaction test for detecting interactions between genetic marker sets and environment in genome-wide studies. G3: Genes, Genomes, Genetics 2024, 15: jkae263. PMID: 39538414, PMCID: PMC11708225, DOI: 10.1093/g3journal/jkae263.Peer-Reviewed Original ResearchGene-environment interactionsStudies of complex diseasesMulti-Ethnic Study of AtherosclerosisComplex diseasesGenetic marker setsGenome-wide analysisGenome-wide studiesHuman complex diseasesGene-alcohol interactionsMulti-Ethnic StudyGenetic main effectsStudy of atherosclerosisSignal transduction pathwaysAssociated with hypertensionBlood pressureSystolic blood pressureGenetic markersEnvironmental factorsAlcohol intakeGenetic variantsTransduction pathwaysSurvival pathwaysMarker setsPathway analysisRare variantsSex differences in proteomics of cardiovascular disease: results from the Yale-CMD registry
Liu Y, Wang Z, Collins S, Testani J, Kleinstein S, Safdar B. Sex differences in proteomics of cardiovascular disease: results from the Yale-CMD registry. European Heart Journal 2024, 45: ehae666.3091. DOI: 10.1093/eurheartj/ehae666.3091.Peer-Reviewed Original ResearchCoronary microvascular dysfunctionCoronary artery diseaseUpregulation of lipidCardiovascular diseaseAcute heart failureCoronary artery disease cohortHistory of diabetesPathophysiology of CVDProximity extension assayBody mass indexSignificant sex differencesRegulation of blood flowSerum proteomic profilesSex differencesProteomic profilingAngiogenesis-related proteinsCardiac PET/CTHemodynamic instabilityIschemic symptomsMicrovascular dysfunctionFalse discovery rateHeart failureFebrile illnessFunctional pathway analysisMass indexSDePER: a hybrid machine learning and regression method for cell-type deconvolution of spatial barcoding-based transcriptomic data
Liu Y, Li N, Qi J, Xu G, Zhao J, Wang N, Huang X, Jiang W, Wei H, Justet A, Adams T, Homer R, Amei A, Rosas I, Kaminski N, Wang Z, Yan X. SDePER: a hybrid machine learning and regression method for cell-type deconvolution of spatial barcoding-based transcriptomic data. Genome Biology 2024, 25: 271. PMID: 39402626, PMCID: PMC11475911, DOI: 10.1186/s13059-024-03416-2.Peer-Reviewed Original ResearchDetecting time‐varying genetic effects in Alzheimer's disease using a longitudinal genome‐wide association studies model
Zhuang X, Xu G, Amei A, Cordes D, Wang Z, Oh E, Initiative F. Detecting time‐varying genetic effects in Alzheimer's disease using a longitudinal genome‐wide association studies model. Alzheimer's & Dementia Diagnosis Assessment & Disease Monitoring 2024, 16: e12597. PMID: 38855650, PMCID: PMC11157162, DOI: 10.1002/dad2.12597.Peer-Reviewed Original ResearchGenome-wide association studiesSingle nucleotide polymorphismsLongitudinal genome-wide association studiesGWAS modelsAssociation studiesGenetic effectsAlzheimer's diseaseSingle nucleotide polymorphism effectsNational Alzheimer's Coordinating Center dataAge-dependent genetic effectsImpairment statusProgression of Alzheimer's diseaseEffects of apoEAge-stratified analysesGenetic signalsGenetic lociNucleotide polymorphismsLongitudinal phenotypesPathway analysisInitiative participantsAmyloid accumulationAmyloidStandardized uptake value ratioCenter dataAmyloid positron emission tomographyComputationally inferred cell-type specific epigenome-wide DNA methylation analysis unveils distinct methylation patterns among immune cells for HIV infection in three cohorts
Zhang X, Hu Y, Vandenhoudt R, Yan C, Marconi V, Cohen M, Wang Z, Justice A, Aouizerat B, Xu K. Computationally inferred cell-type specific epigenome-wide DNA methylation analysis unveils distinct methylation patterns among immune cells for HIV infection in three cohorts. PLOS Pathogens 2024, 20: e1012063. PMID: 38466776, PMCID: PMC10957090, DOI: 10.1371/journal.ppat.1012063.Peer-Reviewed Original ResearchCD4+ T cellsEpigenome-wide association studiesPeripheral blood mononuclear cellsHIV infectionHIV pathogenesisT cellsCpG sitesNatural killer (NK) cellsCell typesAssociated with HIV infectionCD8+ T cellsMethylation patternsCpG methylationDNA methylationEpigenome-wide DNA methylation analysisBlood mononuclear cellsImmune cell typesDifferentially methylated CpG sitesUnique CpG sitesDifferential CpG methylationDNA methylation analysisSignificant CpG sitesArray-based methodsGene Set Enrichment AnalysisComputational deconvolution methodsRETROSPECTIVE VARYING COEFFICIENT ASSOCIATION ANALYSIS OF LONGITUDINAL BINARY TRAITS: APPLICATION TO THE IDENTIFICATION OF GENETIC LOCI ASSOCIATED WITH HYPERTENSION.
Xu G, Amei A, Wu W, Liu Y, Shen L, Oh E, Wang Z. RETROSPECTIVE VARYING COEFFICIENT ASSOCIATION ANALYSIS OF LONGITUDINAL BINARY TRAITS: APPLICATION TO THE IDENTIFICATION OF GENETIC LOCI ASSOCIATED WITH HYPERTENSION. The Annals Of Applied Statistics 2024, 18: 487-505. PMID: 38577266, PMCID: PMC10994004, DOI: 10.1214/23-aoas1798.Peer-Reviewed Original Research
2023
Transformer with convolution and graph-node co-embedding: An accurate and interpretable vision backbone for predicting gene expressions from local histopathological image
Xiao X, Kong Y, Li R, Wang Z, Lu H. Transformer with convolution and graph-node co-embedding: An accurate and interpretable vision backbone for predicting gene expressions from local histopathological image. Medical Image Analysis 2023, 91: 103040. PMID: 38007979, DOI: 10.1016/j.media.2023.103040.Peer-Reviewed Original ResearchConceptsHistopathological imagesVision backbonesGlobal featuresCombination of convolutional layersEncoding of local featuresGraph neural networksHistopathological image analysisGPU consumptionTransformer encoderConvolutional layersGraph-nodesLocal featuresNeural networkMinimal memoryCo-embeddingLow interpretabilityPersonal computerPathological imagesData modelSlide imagesHealth applicationsSuperior accuracyModel complexityInformation predictionHistological imagesBrain Registration and Evaluation for Zebrafish (BREEZE)-mapping: A pipeline for whole-brain structural and activity analyses
Jin D, Neelakantan U, Lacadie C, Chen T, Rooney B, Liu Y, Wu W, Wang Z, Papademetris X, Hoffman E. Brain Registration and Evaluation for Zebrafish (BREEZE)-mapping: A pipeline for whole-brain structural and activity analyses. STAR Protocols 2023, 4: 102647. PMID: 37897734, PMCID: PMC10641303, DOI: 10.1016/j.xpro.2023.102647.Peer-Reviewed Original ResearchCorrection: iDESC: identifying differential expression in single-cell RNA sequencing data with multiple subjects
Liu Y, Zhao J, Adams T, Wang N, Schupp J, Wu W, McDonough J, Chupp G, Kaminski N, Wang Z, Yan X. Correction: iDESC: identifying differential expression in single-cell RNA sequencing data with multiple subjects. BMC Bioinformatics 2023, 24: 394. PMID: 37858060, PMCID: PMC10588114, DOI: 10.1186/s12859-023-05523-6.Peer-Reviewed Original ResearchtRFtarget 2.0: expanding the targetome landscape of transfer RNA-derived fragments
Li N, Yao S, Yu G, Lu L, Wang Z. tRFtarget 2.0: expanding the targetome landscape of transfer RNA-derived fragments. Nucleic Acids Research 2023, 52: d345-d350. PMID: 37811890, PMCID: PMC10767876, DOI: 10.1093/nar/gkad815.Peer-Reviewed Original ResearchCis-meQTL for cocaine use-associated DNA methylation in an HIV-positive cohort show pleiotropic effects on multiple traits
Cheng Y, Justice A, Wang Z, Li B, Hancock D, Johnson E, Xu K. Cis-meQTL for cocaine use-associated DNA methylation in an HIV-positive cohort show pleiotropic effects on multiple traits. BMC Genomics 2023, 24: 556. PMID: 37730558, PMCID: PMC10510240, DOI: 10.1186/s12864-023-09661-2.Peer-Reviewed Original ResearchConceptsDNA methylationMultiple traitsPleiotropic effectsGenetic variantsAberrant DNA methylationPhenome-wide association studyCis-meQTLsComplex traitsRelevant traitsDNAm sitesEnrichment analysisMeQTLsAssociation studiesSignificant traitsTraitsImmune pathwaysMethylationNew insightsMendelian randomizationImmunological functionsGenesVariantsCausal rolePathwayCpGiDESC: identifying differential expression in single-cell RNA sequencing data with multiple subjects
Liu Y, Zhao J, Adams T, Wang N, Schupp J, Wu W, McDonough J, Chupp G, Kaminski N, Wang Z, Yan X. iDESC: identifying differential expression in single-cell RNA sequencing data with multiple subjects. BMC Bioinformatics 2023, 24: 318. PMID: 37608264, PMCID: PMC10463720, DOI: 10.1186/s12859-023-05432-8.Peer-Reviewed Original ResearchDifferences in Mortality Among Patients With Asthma and COPD Hospitalized With COVID-19
Liu Y, Rajeevan H, Simonov M, Lee S, Wilson F, Desir G, Vinetz J, Yan X, Wang Z, Clark B, Possick J, Price C, Lutchmansingh D, Ortega H, Zaeh S, Gomez J, Cohn L, Gautam S, Chupp G. Differences in Mortality Among Patients With Asthma and COPD Hospitalized With COVID-19. The Journal Of Allergy And Clinical Immunology In Practice 2023, 11: 3383-3390.e3. PMID: 37454926, PMCID: PMC10787810, DOI: 10.1016/j.jaip.2023.07.006.Peer-Reviewed Original ResearchConceptsChronic obstructive pulmonary diseaseType 2 inflammationCOVID-19 severitySOFA scoreAirway diseaseNoneosinophilic asthmaSequential Organ Failure Assessment scoreOrgan Failure Assessment scoreSevere coronavirus disease 2019Higher SOFA scoreMedian SOFA scoreRetrospective cohort studyObstructive pulmonary diseaseOdds of mortalityLower SOFA scoresCells/μLCOVID-19 outcomesCoronavirus disease 2019Logistic regression analysisCOVID-19Clinical confoundersAsthma patientsCohort studyImmunological factorsClinical featuresDeep learning-based morphological feature analysis and the prognostic association study in colon adenocarcinoma histopathological images
Xiao X, Wang Z, Kong Y, Lu H. Deep learning-based morphological feature analysis and the prognostic association study in colon adenocarcinoma histopathological images. Frontiers In Oncology 2023, 13: 1081529. PMID: 36845699, PMCID: PMC9945212, DOI: 10.3389/fonc.2023.1081529.Peer-Reviewed Original Research
2022
Computational and Statistical Methods for Single-Cell RNA Sequencing Data
Wang Z, Yan X. Computational and Statistical Methods for Single-Cell RNA Sequencing Data. Springer Handbooks Of Computational Statistics 2022, 3-35. DOI: 10.1007/978-3-662-65902-1_1.ChaptersSingle-cell RNA sequencing technologySingle-cell RNA sequencing dataRNA sequencing technologyPhenotype of interestRNA sequencing dataDifferential expression analysisScRNA-seq dataStatistical methodsSequencing technologiesExpression analysisDropout imputationSequencing dataSeq dataDroplet-based technologiesDropout eventsDisease pathogenesisPopulation composition changesData normalizationHigh noise levelsPhenotypeNoise levelTherapeuticsComposition changes
2020
tRFtarget: a database for transfer RNA-derived fragment targets
Li N, Shan N, Lu L, Wang Z. tRFtarget: a database for transfer RNA-derived fragment targets. Nucleic Acids Research 2020, 49: d254-d260. PMID: 33035346, PMCID: PMC7779015, DOI: 10.1093/nar/gkaa831.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsBase PairingBase SequenceCaenorhabditis elegansDatabases, Nucleic AcidDrosophila melanogasterGene OntologyHumansMiceMolecular Sequence AnnotationNucleic Acid ConformationNucleic Acid HybridizationRhodobacter sphaeroidesRNA, MessengerRNA, Small UntranslatedRNA, TransferSchizosaccharomycesThermodynamicsXenopusZebrafishConceptsTarget genesTransfer RNASmall non-coding RNAsGene Ontology annotationsNon-coding RNAsFunctional pathway analysisAccessible web-based databaseMolecular functionsOntology annotationsBiological functionsPathway analysisMolecular mechanismsPhysiological processesTarget predictionHuman diseasesGenesMRNA transcriptsRNAWeb-based databaseConvenient linkTRFImportant roleRNAhybridTargetIntaRNA
2019
Maximum likelihood estimation of nonlinear mixed-effects models with crossed random effects by combining first-order conditional linearization and sequential quadratic programming
Fu L, Wang M, Wang Z, Song X, Tang S. Maximum likelihood estimation of nonlinear mixed-effects models with crossed random effects by combining first-order conditional linearization and sequential quadratic programming. International Journal Of Biomathematics 2019, 12: 1950040. DOI: 10.1142/s1793524519500402.Peer-Reviewed Original ResearchSequential quadratic programmingNLME modelsMaximum likelihood estimationNonlinear mixed effects modelsParameter estimationQuadratic programmingGeneral formulationLikelihood estimationRandom effectsStandard statistical packagesVariance-covariance matrixModel linearizationMethod convergesConditional expansionComputational algorithmComputational optimizationNormal assumptionNLME modelingError termSimulation studyLinearizationMixed effects modelsEstimationHigh accuracyAlgorithm
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