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MultiK: an automated tool to determine optimal cluster numbers in single-cell RNA sequencing data.
Liu, Siyao; Thennavan, Aatish; Garay, Joseph P; Marron, J S; Perou, Charles M.
Affiliation
  • Liu S; Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Marsico Hall, 5th floor, CB#7599, 125 Mason Farm Road, Chapel Hill, NC, 27599, USA.
  • Thennavan A; Department of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
  • Garay JP; Curriculum in Bioinformatics and Computational Biology, University of North Carolina, Chapel Hill, NC, 27599, USA.
  • Marron JS; Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Marsico Hall, 5th floor, CB#7599, 125 Mason Farm Road, Chapel Hill, NC, 27599, USA.
  • Perou CM; Oral and Craniofacial Biomedicine Program, School of Dentistry, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
Genome Biol ; 22(1): 232, 2021 08 19.
Article in En | MEDLINE | ID: mdl-34412669
Single-cell RNA sequencing (scRNA-seq) provides new opportunities to characterize cell populations, typically accomplished through some type of clustering analysis. Estimation of the optimal cluster number (K) is a crucial step but often ignored. Our approach improves most current scRNA-seq cluster methods by providing an objective estimation of the number of groups using a multi-resolution perspective. MultiK is a tool for objective selection of insightful Ks and achieves high robustness through a consensus clustering approach. We demonstrate that MultiK identifies reproducible groups in scRNA-seq data, thus providing an objective means to estimating the number of possible groups or cell-type populations present.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software / Sequence Analysis, RNA / Single-Cell Analysis Limits: Animals / Humans Language: En Journal: Genome Biol Journal subject: BIOLOGIA MOLECULAR / GENETICA Year: 2021 Document type: Article Affiliation country: United States Country of publication: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Software / Sequence Analysis, RNA / Single-Cell Analysis Limits: Animals / Humans Language: En Journal: Genome Biol Journal subject: BIOLOGIA MOLECULAR / GENETICA Year: 2021 Document type: Article Affiliation country: United States Country of publication: United kingdom