2022
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 variation
2021
Pre-existing chromatin accessibility and gene expression differences among naive CD4+ T cells influence effector potential
Rogers D, Sood A, Wang H, van Beek J, Rademaker T, Artusa P, Schneider C, Shen C, Wong D, Bhagrath A, Lebel M, Condotta S, Richer M, Martins A, Tsang J, Barreiro L, François P, Langlais D, Melichar H, Textor J, Mandl J. Pre-existing chromatin accessibility and gene expression differences among naive CD4+ T cells influence effector potential. Cell Reports 2021, 37: 110064. PMID: 34852223, DOI: 10.1016/j.celrep.2021.110064.Peer-Reviewed Original ResearchConceptsSingle-cell RNA sequencingGene expression differencesCell receptor signalingChromatin accessibilityLineage choiceTCR signal strengthCell chromatinTranscriptional differencesRNA sequencingExpression differencesReceptor signalingLandscape differencesEffector potentialEffector lineagesThymic developmentCellsNaive CD4Self-peptide MHCChromatinCognate antigenLineagesGenesSignalingTCR interactionsKey drivers
2020
Broad immune activation underlies shared set point signatures for vaccine responsiveness in healthy individuals and disease activity in patients with lupus
Kotliarov Y, Sparks R, Martins A, Mulè M, Lu Y, Goswami M, Kardava L, Banchereau R, Pascual V, Biancotto A, Chen J, Schwartzberg P, Bansal N, Liu C, Cheung F, Moir S, Tsang J. Broad immune activation underlies shared set point signatures for vaccine responsiveness in healthy individuals and disease activity in patients with lupus. Nature Medicine 2020, 26: 618-629. PMID: 32094927, PMCID: PMC8392163, DOI: 10.1038/s41591-020-0769-8.Peer-Reviewed Original ResearchMeSH KeywordsAdaptive ImmunityAdolescentAdultAgedAged, 80 and overAntibody FormationB-LymphocytesChildChild, PreschoolCohort StudiesFemaleGene Expression ProfilingHumansInfluenza VaccinesInfluenza, HumanLupus Erythematosus, SystemicMaleMiddle AgedTranscriptomeVaccinationYellow FeverYellow Fever VaccineYoung AdultConceptsDisease activityVaccine responsivenessAutoimmune disease activityBlood transcriptional signaturesYellow fever vaccinationSystemic lupus erythematosusClinical quiescenceFever vaccinationLupus erythematosusCancer immunotherapyBaseline predictorsDisease outcomeHealthy subjectsImmune responseI IFNHealthy individualsVaccinationTranscriptional signatureImmune variationBaseline statePatientsExtent of activationBiological basisSurface proteinsInfection responseCancer prognosis with shallow tumor RNA sequencing
Milanez-Almeida P, Martins A, Germain R, Tsang J. Cancer prognosis with shallow tumor RNA sequencing. Nature Medicine 2020, 26: 188-192. PMID: 32042193, DOI: 10.1038/s41591-019-0729-3.Peer-Reviewed Original ResearchConceptsCancer prognosisTumor RNA-seq dataTumor RNA sequencingPrediction of outcomeTypes of cancerClinical outcomesRNA sequencingAdverse outcomesRelative riskDisease outcomeOutcome predictionTumor RNA-seqPersonalized oncologyTranscriptional signatureCancer1–3Molecular pathwaysOutcomesPrognosisLongitudinal analysisTranscriptional pathwaysCancer
2017
Transcriptional Response of Respiratory Epithelium to Nontuberculous Mycobacteria
Matsuyama M, Martins A, Shallom S, Kamenyeva O, Kashyap A, Sampaio E, Kabat J, Olivier K, Zelazny A, Tsang J, Holland S. Transcriptional Response of Respiratory Epithelium to Nontuberculous Mycobacteria. American Journal Of Respiratory Cell And Molecular Biology 2017, 58: 241-252. PMID: 28915071, PMCID: PMC5806000, DOI: 10.1165/rcmb.2017-0218oc.Peer-Reviewed Original ResearchConceptsCholesterol biosynthesisUpregulation of genesRespiratory epitheliumGene expression signaturesCiliary genesTranscriptional responseRNA sequencingEpithelial cell infectionResponse genesInflammatory response genesHost responseCytokine/chemokine productionRespiratory epithelial cell culturesEpithelial cell culturesPulmonary nontuberculous mycobacteria (NTM) diseaseExpression signaturesMajor host responsesCytokines/chemokinesGenesRespiratory epithelial cellsCiliary functionNontuberculous mycobacteria diseaseCell infectionMultiplicity of infectionBiosynthesis
2016
Robust Inference of Cell-to-Cell Expression Variations from Single- and K-Cell Profiling
Narayanan M, Martins A, Tsang J. Robust Inference of Cell-to-Cell Expression Variations from Single- and K-Cell Profiling. PLOS Computational Biology 2016, 12: e1005016. PMID: 27438699, PMCID: PMC4954693, DOI: 10.1371/journal.pcbi.1005016.Peer-Reviewed Original ResearchMeSH KeywordsComputational BiologyGene Expression ProfilingHumansMacrophagesModels, BiologicalModels, StatisticalRNA, MessengerSingle-Cell AnalysisConceptsSingle-cell expression levelsExpression levelsNovel biological informationSingle cellsKey inflammatory genesExpression variationGene expressionCellular heterogeneityBiological informationRandom poolSingle populationHuman macrophagesBiological conditionsCell populationsGenesMultiplexed technologiesK cellsInflammatory genesCellsBiological varianceQuantifying differencesSensitive technologyContinuous variationRobust inferenceProfiling