title: Power analysis of single-cell RNA-sequencing experiments.
abstract: Single-cell RNA sequencing (scRNA-seq) has become an established and powerful method to investigate transcriptomic cell-to-cell variation, thereby revealing new cell types and providing insights into developmental processes and transcriptional stochasticity. A key question is how the variety of available protocols compare in terms of their ability to detect and accurately quantify gene expression. Here, we assessed the protocol sensitivity and accuracy of many published data sets, on the basis of spike-in standards and uniform data processing. For our workflow, we developed a flexible tool for counting the number of unique molecular identifiers (https://github.com/vals/umis/). We compared 15 protocols computationally and 4 protocols experimentally for batch-matched cell populations, in addition to investigating the effects of spike-in molecular degradation. Our analysis provides an integrated framework for comparing scRNA-seq protocols.
authors.affiliation: European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.
authors.forename: Valentine
authors.initials: V
authors.lastname: Svensson
authors.affiliation: European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.
authors.forename: Kedar Nath
authors.initials: KN
authors.lastname: Natarajan
authors.affiliation: Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.
authors.forename: Lam-Ha
authors.initials: LH
authors.lastname: Ly
authors.affiliation: Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.|Centre of Biological Engineering, University of Minho, Campus de Gualtar, Braga, Portugal.
authors.forename: Ricardo J
authors.initials: RJ
authors.lastname: Miragaia
authors.affiliation: Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.|Wellcome Trust - Medical Research Council Cambridge Stem Cell Institute, Cambridge, UK.|Department of Haematology, University of Cambridge, Cambridge, UK.
authors.forename: Charlotte
authors.initials: C
authors.lastname: Labalette
authors.affiliation: Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.
authors.forename: Iain C
authors.initials: IC
authors.lastname: Macaulay
authors.affiliation: Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.|Wellcome Trust - Medical Research Council Cambridge Stem Cell Institute, Cambridge, UK.|Department of Haematology, University of Cambridge, Cambridge, UK.
authors.forename: Ana
authors.initials: A
authors.lastname: Cvejic
authors.affiliation: European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.
authors.forename: Sarah A
authors.initials: SA
authors.lastname: Teichmann
mesh_terms: D000818:Animals; D053595:Embryonic Stem Cells / Q000502:physiology; D005615:Freezing; D051379:Mice; D011061:Poly A; D012333:RNA, Messenger; D012680:Sensitivity and Specificity; D017423:Sequence Analysis, RNA / Q000379:methods* / Q000592:standards / Q000706:statistics & numerical data; D059010:Single-Cell Analysis / Q000379:methods* / Q000592:standards / Q000706:statistics & numerical data; D057188:Workflow
chemical_list: D012333:RNA, Messenger; D011061:Poly A