2024
Quantifying cell-state densities in single-cell phenotypic landscapes using Mellon
Otto D, Jordan C, Dury B, Dien C, Setty M. Quantifying cell-state densities in single-cell phenotypic landscapes using Mellon. Nature Methods 2024, 21: 1185-1195. PMID: 38890426, DOI: 10.1038/s41592-024-02302-w.Peer-Reviewed Original Research
2023
SEACells infers transcriptional and epigenomic cellular states from single-cell genomics data
Persad S, Choo Z, Dien C, Sohail N, Masilionis I, Chaligné R, Nawy T, Brown C, Sharma R, Pe’er I, Setty M, Pe’er D. SEACells infers transcriptional and epigenomic cellular states from single-cell genomics data. Nature Biotechnology 2023, 41: 1746-1757. PMID: 36973557, PMCID: PMC10713451, DOI: 10.1038/s41587-023-01716-9.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsCD4-Positive T-LymphocytesChromatinEpigenomicsGenomicsHumansSingle-Cell AnalysisConceptsCell statesTransposase-accessible chromatinSingle-cell sequencing dataSingle-cell dataDiscrete cell typesChromatin landscapeSequence dataGenomic dataExpression dynamicsAssociated with disease onsetCritical regulatorsGene scoreT cell differentiationCD4 T cell differentiationCell typesHematopoietic differentiationMetaCellChromatinCell clustersActive stateDifferentiationATACGenomeCellsRNA
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