2023
scNAT: a deep learning method for integrating paired single-cell RNA and T cell receptor sequencing profiles
Zhu B, Wang Y, Ku L, van Dijk D, Zhang L, Hafler D, Zhao H. scNAT: a deep learning method for integrating paired single-cell RNA and T cell receptor sequencing profiles. Genome Biology 2023, 24: 292. PMID: 38111007, PMCID: PMC10726524, DOI: 10.1186/s13059-023-03129-y.Peer-Reviewed Original Research
2014
Joint Modeling and Registration of Cell Populations in Cohorts of High-Dimensional Flow Cytometric Data
Pyne S, Lee SX, Wang K, Irish J, Tamayo P, Nazaire MD, Duong T, Ng SK, Hafler D, Levy R, Nolan GP, Mesirov J, McLachlan GJ. Joint Modeling and Registration of Cell Populations in Cohorts of High-Dimensional Flow Cytometric Data. PLOS ONE 2014, 9: e100334. PMID: 24983991, PMCID: PMC4077578, DOI: 10.1371/journal.pone.0100334.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsCluster AnalysisComputational BiologyComputer SimulationFlow CytometryHumansSoftwareConceptsMultivariate probability distributionProbability distributionMultivariate responseJCM modelMultiple experimental conditionsJoint modelingJoint clusteringSimultaneous modelingComputational methodsRegistration of populationTypical experimentModelingNew samplesModelJCMFlow cytometric dataMultiparametric cytometrySystem-level variationApplications
2012
An RNA Profile Identifies Two Subsets of Multiple Sclerosis Patients Differing in Disease Activity
Ottoboni L, Keenan BT, Tamayo P, Kuchroo M, Mesirov JP, Buckle GJ, Khoury SJ, Hafler DA, Weiner HL, De Jager PL. An RNA Profile Identifies Two Subsets of Multiple Sclerosis Patients Differing in Disease Activity. Science Translational Medicine 2012, 4: 153ra131. PMID: 23019656, PMCID: PMC3753678, DOI: 10.1126/scitranslmed.3004186.Peer-Reviewed Original ResearchConceptsGlatiramer acetateDisease activityPatient populationFirst-line disease-modifying treatmentsMultiple sclerosis (MS) patient populationPeripheral blood mononuclear cellsMS patient populationDisease-modifying treatmentsMultiple sclerosis patientsBlood mononuclear cellsSubset of subjectsDisease courseSclerosis patientsMS subjectsMononuclear cellsInflammatory eventsTreatment responseUntreated subjectsAdditional groupHigh expressionTranscriptional signatureSubjectsRNA profilesTreatmentTranscriptional profiles
2011
Pervasive Sharing of Genetic Effects in Autoimmune Disease
Cotsapas C, Voight BF, Rossin E, Lage K, Neale BM, Wallace C, Abecasis GR, Barrett JC, Behrens T, Cho J, De Jager PL, Elder JT, Graham RR, Gregersen P, Klareskog L, Siminovitch KA, van Heel DA, Wijmenga C, Worthington J, Todd JA, Hafler DA, Rich SS, Daly MJ, . Pervasive Sharing of Genetic Effects in Autoimmune Disease. PLOS Genetics 2011, 7: e1002254. PMID: 21852963, PMCID: PMC3154137, DOI: 10.1371/journal.pgen.1002254.Peer-Reviewed Original ResearchConceptsSingle nucleotide polymorphismsSystemic lupus erythematosusImmune-mediated diseasesType 1 diabetesGenetic risk factorsMajor histocompatibility locusCommon autoimmuneCommon single nucleotide polymorphismsLupus erythematosusCrohn's diseaseRheumatoid arthritisClinical evidenceMultiple sclerosisAutoimmune diseasesRisk single nucleotide polymorphismsCeliac diseaseInflammatory diseasesRisk factorsMeta-AnalysisDisease riskDiseaseHistocompatibility locusUnderlying mechanismGenetic associationNucleotide polymorphisms