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Assessing the reliability of spike-in normalization for analyses of single-cell RNA sequencing data
Aaron T. L. Lun, Fernando J. Calero-Nieto, Liora Haim-Vilmovsky, Berthold Göttgens, John C. Marioni
doi: https://doi.org/10.1101/119784
Aaron T. L. Lun
1Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, United Kingdom
Fernando J. Calero-Nieto
2Wellcome Trust and MRC Cambridge Stem Cell Institute, University of Cambridge, Wellcome Trust/MRC Building, Hills Road, Cambridge CB2 0XY, United Kingdom
Liora Haim-Vilmovsky
3EMBL European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
4Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, United Kingdom
Berthold Göttgens
2Wellcome Trust and MRC Cambridge Stem Cell Institute, University of Cambridge, Wellcome Trust/MRC Building, Hills Road, Cambridge CB2 0XY, United Kingdom
John C. Marioni
1Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, United Kingdom
3EMBL European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, United Kingdom
4Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, United Kingdom
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Posted March 23, 2017.
Assessing the reliability of spike-in normalization for analyses of single-cell RNA sequencing data
Aaron T. L. Lun, Fernando J. Calero-Nieto, Liora Haim-Vilmovsky, Berthold Göttgens, John C. Marioni
bioRxiv 119784; doi: https://doi.org/10.1101/119784
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