SC3: consensus clustering of single-cell RNA-seq data

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Authors
Kiselev, VY
Kirschner, K
Schaub, MT
Andrews, T
Yiu, A
Chandra, T
Natarajan, KN
Publication Date
2017-05-01
Journal Title
Nature Methods
ISSN
1548-7091
Publisher
Nature Publishing Group
Volume
14
Issue
5
Pages
483-486
Language
English
Type
Article
This Version
AM
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Citation
Kiselev, V., Kirschner, K., Schaub, M., Andrews, T., Yiu, A., Chandra, T., Natarajan, K., et al. (2017). SC3: consensus clustering of single-cell RNA-seq data. Nature Methods, 14 (5), 483-486. https://doi.org/10.1038/nmeth.4236
Abstract
Single-cell RNA-seq enables the quantitative characterization of cell types based on global transcriptome profiles. We present single-cell consensus clustering (SC3), a user-friendly tool for unsupervised clustering, which achieves high accuracy and robustness by combining multiple clustering solutions through a consensus approach (http://bioconductor.org/packages/SC3). We demonstrate that SC3 is capable of identifying subclones from the transcriptomes of neoplastic cells collected from patients.
Keywords
gene expression, machine learning, RNA sequencing, software
Sponsorship
V.Y.K., T.A., A.Y. and M.H. are supported by Wellcome Trust Grants. K.N.N. is supported by the Wellcome Trust Strategic Award 'Single cell genomics of mouse gastrulation'. M.T.S. acknowledges support from FRS-FNRS; the Belgian Network DYSCO (Dynamical Systems, Control and Optimisation), funded by the Interuniversity Attraction Poles Programme initiated by the Belgian State Science Policy Office; and the ARC (Action de Recherche Concerte) on Mining and Optimization of Big Data Models, funded by the Wallonia-Brussels Federation. M.B. acknowledges support from EPSRC (grant EP/N014529/1). T.C. was funded through a core funded fellowship by the Sanger Institute and a Chancellor′s fellowship from the University of Edinburgh. K.K. and A.R.G. are supported by Bloodwise (grant ref. 13003), the Wellcome Trust (grant ref. 104710/Z/14/Z), the Medical Research Council, the Kay Kendall Leukaemia Fund, the Cambridge NIHR Biomedical Research Center, the Cambridge Experimental Cancer Medicine Centre, the Leukemia and Lymphoma Society of America (grant ref. 07037) and a core support grant from the Wellcome Trust and MRC to the Wellcome Trust-Medical Research Council Cambridge Stem Cell Institute. W.R. was supported by BBSRC (grant ref. BB/K010867/1), the Wellcome Trust (grant ref. 095645/Z/11/Z), EU BLUEPRINT and EpiGeneSys.
Funder references
MRC (MC_PC_12009)
WELLCOME TRUST (104710/Z/14/Z)
Identifiers
External DOI: https://doi.org/10.1038/nmeth.4236
This record's URL: https://www.repository.cam.ac.uk/handle/1810/264381

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