title: Single-cell mRNA quantification and differential analysis with Census.
abstract: Single-cell gene expression studies promise to reveal rare cell types and cryptic states, but the high variability of single-cell RNA-seq measurements frustrates efforts to assay transcriptional differences between cells. We introduce the Census algorithm to convert relative RNA-seq expression levels into relative transcript counts without the need for experimental spike-in controls. Analyzing changes in relative transcript counts led to dramatic improvements in accuracy compared to normalized read counts and enabled new statistical tests for identifying developmentally regulated genes. Census counts can be analyzed with widely used regression techniques to reveal changes in cell-fate-dependent gene expression, splicing patterns and allelic imbalances. We reanalyzed single-cell data from several developmental and disease studies, and demonstrate that Census enabled robust analysis at multiple layers of gene regulation. Census is freely available through our updated single-cell analysis toolkit, Monocle 2.
authors.affiliation: Department of Genome Sciences, University of Washington, Seattle, Washington, USA.|Molecular and Cellular Biology Program, University of Washington, Seattle, Washington, USA.
authors.forename: Xiaojie
authors.initials: X
authors.lastname: Qiu
authors.affiliation: Department of Genome Sciences, University of Washington, Seattle, Washington, USA.
authors.forename: Andrew
authors.initials: A
authors.lastname: Hill
authors.affiliation: Department of Genome Sciences, University of Washington, Seattle, Washington, USA.
authors.forename: Jonathan
authors.initials: J
authors.lastname: Packer
authors.affiliation: Department of Genome Sciences, University of Washington, Seattle, Washington, USA.
authors.forename: Dejun
authors.initials: D
authors.lastname: Lin
authors.affiliation: Department of Applied Mathematics, University of Washington, Seattle, Washington, USA.
authors.forename: Yi-An
authors.initials: YA
authors.lastname: Ma
authors.affiliation: Department of Genome Sciences, University of Washington, Seattle, Washington, USA.|Molecular and Cellular Biology Program, University of Washington, Seattle, Washington, USA.
authors.forename: Cole
authors.identifier: 0000-0002-8105-4347
authors.initials: C
authors.lastname: Trapnell
mesh_terms: D000465:Algorithms; D020869:Gene Expression Profiling / Q000379:methods*; D005786:Gene Expression Regulation; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D012313:RNA / Q000235:genetics*; D017423:Sequence Analysis, RNA / Q000379:methods*; D059010:Single-Cell Analysis / Q000379:methods*; D059467:Transcriptome / Q000235:genetics
chemical_list: D012313:RNA