2023
A statistical framework to identify cell types whose genetically regulated proportions are associated with complex diseases
Liu W, Deng W, Chen M, Dong Z, Zhu B, Yu Z, Tang D, Sauler M, Lin C, Wain L, Cho M, Kaminski N, Zhao H. A statistical framework to identify cell types whose genetically regulated proportions are associated with complex diseases. PLOS Genetics 2023, 19: e1010825. PMID: 37523391, PMCID: PMC10414598, DOI: 10.1371/journal.pgen.1010825.Peer-Reviewed Original ResearchConceptsCell typesDisease-associated tissuesWide association studyComplex diseasesCell type proportionsDisease-relevant tissuesReal GWAS dataFunctional genesTranscriptomic dataGWAS dataGenetic dataAssociation studiesNovel statistical frameworkChronic obstructive pulmonary diseaseStatistical frameworkObstructive pulmonary diseaseIdiopathic pulmonary fibrosisBreast cancer riskType proportionsBlood CD8Pulmonary diseasePulmonary fibrosisPredictive biomarkersLung tissueBreast cancerEmergence of division of labor in tissues through cell interactions and spatial cues
Adler M, Moriel N, Goeva A, Avraham-Davidi I, Mages S, Adams T, Kaminski N, Macosko E, Regev A, Medzhitov R, Nitzan M. Emergence of division of labor in tissues through cell interactions and spatial cues. Cell Reports 2023, 42: 112412. PMID: 37086403, PMCID: PMC10242439, DOI: 10.1016/j.celrep.2023.112412.Peer-Reviewed Original ResearchConceptsSingle-cell RNA sequencingMost cell typesCell-type populationsCell-cell interactionsDistinguishable expression patternsCell population levelSpatial transcriptomics dataCell interactionsLigand-receptor networkMulticellular organismsTranscriptomic dataRNA sequencingInstructive signalsExpression patternsSpecialist cellsCell typesIndividual cellsDivision of laborMultiple functionsTissue environmentSame cellsDifferent functionsPopulation levelCellsDivision
2022
Comprehensive visualization of cell–cell interactions in single-cell and spatial transcriptomics with NICHES
Raredon M, Yang J, Kothapalli N, Lewis W, Kaminski N, Niklason L, Kluger Y. Comprehensive visualization of cell–cell interactions in single-cell and spatial transcriptomics with NICHES. Bioinformatics 2022, 39: btac775. PMID: 36458905, PMCID: PMC9825783, DOI: 10.1093/bioinformatics/btac775.Peer-Reviewed Original ResearchConceptsCell-cell interactionsCell-cell signalingSingle-cell resolutionSingle-cell dataLocal cellular microenvironmentSingle-cell levelSpatial transcriptomics dataCell clustersExtracellular signalingTranscriptomic dataGene expression valuesSpatial transcriptomicsSignaling mechanismCellular microenvironmentNicheExpression valuesSupplementary dataSignalingTranscriptomicsComprehensive visualizationBioinformaticsInteraction
2017
Transcriptome profiles in sarcoidosis and their potential role in disease prediction
Schupp JC, Vukmirovic M, Kaminski N, Prasse A. Transcriptome profiles in sarcoidosis and their potential role in disease prediction. Current Opinion In Pulmonary Medicine 2017, 23: 487-492. PMID: 28590292, PMCID: PMC5637542, DOI: 10.1097/mcp.0000000000000403.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsGenome-wide expression studiesWide expression studiesTranscriptome profilesTranscriptomic dataRNA sequencingExpression studiesGene expressionMolecular mechanismsLarge prospective followTh1 immune responseTranscriptomeNonnecrotizing granulomasProspective followSystemic diseaseDisease progressionTreatment outcomesImmune responseSarcoidosisPotential roleControl tissuesProgressive sarcoidosisKey roleDiseaseTranscriptomicsGranulomas