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SC3 - consensus clustering of single-cell RNA-Seq data
View ORCID ProfileVladimir Yu. Kiselev, Kristina Kirschner, Michael T. Schaub, Tallulah Andrews, Tamir Chandra, Kedar N Natarajan, Wolf Reik, Mauricio Barahona, Anthony R Green, Martin Hemberg
doi: https://doi.org/10.1101/036558
Vladimir Yu. Kiselev
1Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK
Kristina Kirschner
2Cambridge Institute for Medical Research, Wellcome Trust/MRC Stem Cell Institute and Department of Haematology, University of Cambridge, Hills Road, Cambridge, UK
Michael T. Schaub
3Department of Mathematics and naXys, University of Namur, Belgium
4ICTEAM, Université catholique de Louvain, Belgium
Tallulah Andrews
1Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK
Tamir Chandra
1Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK
5Epigenetics Programme, The Babraham Institute, Babraham, Cambridge, UK
Kedar N Natarajan
1Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK
6EMBL-European Bioinformatics Institute, Hinxton, Cambridge, UK
Wolf Reik
1Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK
5Epigenetics Programme, The Babraham Institute, Babraham, Cambridge, UK
7Centre for Trophoblast Research, University of Cambridge, Cambridge, UK
Mauricio Barahona
8Department of Mathematics, Imperial College London, London, UK
Anthony R Green
2Cambridge Institute for Medical Research, Wellcome Trust/MRC Stem Cell Institute and Department of Haematology, University of Cambridge, Hills Road, Cambridge, UK
Martin Hemberg
1Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK
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Posted April 14, 2016.
SC3 - consensus clustering of single-cell RNA-Seq data
Vladimir Yu. Kiselev, Kristina Kirschner, Michael T. Schaub, Tallulah Andrews, Tamir Chandra, Kedar N Natarajan, Wolf Reik, Mauricio Barahona, Anthony R Green, Martin Hemberg
bioRxiv 036558; doi: https://doi.org/10.1101/036558
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