Featured Publications
Normalizing and denoising protein expression data from droplet-based single cell profiling
Mulè M, Martins A, Tsang J. Normalizing and denoising protein expression data from droplet-based single cell profiling. Nature Communications 2022, 13: 2099. PMID: 35440536, PMCID: PMC9018908, DOI: 10.1038/s41467-022-29356-8.Peer-Reviewed Original ResearchConceptsProtein expression dataSingle-cell profiling methodsExpression dataSingle-cell profilingOligo-conjugated antibodiesTechnical noiseProtein populationCITE-seqCellular heterogeneityComprehensive dissectionDownstream analysisCell profilingDSBsSingle cellsProtein levelsProtein expressionCell populationsOpen-source R packageProfiling methodProtein countsEmpty dropletsR packageComputational analysisCellsBiological variationSystematic Analysis of Cell-to-Cell Expression Variation of T Lymphocytes in a Human Cohort Identifies Aging and Genetic Associations
Lu Y, Biancotto A, Cheung F, Remmers E, Shah N, McCoy J, Tsang J. Systematic Analysis of Cell-to-Cell Expression Variation of T Lymphocytes in a Human Cohort Identifies Aging and Genetic Associations. Immunity 2016, 45: 1162-1175. PMID: 27851916, PMCID: PMC6532399, DOI: 10.1016/j.immuni.2016.10.025.Peer-Reviewed Original ResearchConceptsExpression variationDisease-associated genetic polymorphismsSingle-cell dataPrimary cell populationsCell populationsOrganismal levelFunctional associationDisease susceptibilityGenetic associationFlow cytometry dataCytometry dataGenetic polymorphismsHuman cohortsFlow cytometryCellsHigh-dimensional flow cytometryCell subpopulationsImportant rolePrevalent featureProteinPhenotypeSystematic analysisMultiple baseline measurementsPolymorphismPopulationGlobal Analyses of Human Immune Variation Reveal Baseline Predictors of Postvaccination Responses
Tsang J, Schwartzberg P, Kotliarov Y, Biancotto A, Xie Z, Germain R, Wang E, Olnes M, Narayanan M, Golding H, Moir S, Dickler H, Perl S, Cheung F, Center T, Consortium T, Obermoser G, Chaussabel D, Palucka K, Chen J, Fuchs J, Ho J, Khurana S, King L, Langweiler M, Liu H, Manischewitz J, Pos Z, Posada J, Schum P, Shi R, Valdez J, Wang W, Zhou H, Kastner D, Marincola F, McCoy J, Trinchieri G, Young N. Global Analyses of Human Immune Variation Reveal Baseline Predictors of Postvaccination Responses. Cell 2014, 157: 499-513. PMID: 24725414, PMCID: PMC4139290, DOI: 10.1016/j.cell.2014.03.031.Peer-Reviewed Original ResearchConceptsPre-existing antibody titersPostvaccination antibody responsePeripheral blood mononuclear cell transcriptomeB cell responsesBaseline time pointPostvaccination responsesInfluenza vaccinationImmune monitoringSerum titersAntibody titersAntibody responseBaseline predictorsBaseline differencesImmune parametersHuman immunityCell responsesSubpopulation frequenciesTime pointsCell populationsIntra-individual variationVaccinationTiters
2017
Environment Tunes Propagation of Cell-to-Cell Variation in the Human Macrophage Gene Network
Martins A, Narayanan M, Prüstel T, Fixsen B, Park K, Gottschalk R, Lu Y, Andrews-Pfannkoch C, Lau W, Wendelsdorf K, Tsang J. Environment Tunes Propagation of Cell-to-Cell Variation in the Human Macrophage Gene Network. Cell Systems 2017, 4: 379-392.e12. PMID: 28365150, PMCID: PMC8392141, DOI: 10.1016/j.cels.2017.03.002.Peer-Reviewed Original ResearchConceptsGene networksCellular adaptationCell variationSingle-cell transcriptomic studiesGene-gene correlationsUnderlying regulatory mechanismsDegree of phosphorylationPhenotypic diversityTranscriptomic studiesEnvironmental adaptationMultiple molecular parametersGene expressionRegulatory mechanismsCellular heterogeneityDistinct environmentsSingle cellsHuman macrophagesQuantitative tuningCell populationsNatural perturbationsGenesDifferent environmentsSuch variationCellsStochastic simulation analysis