Characterizing noise structure in single-cell RNA-seq distinguishes genuine from technical stochastic allelic expression

Nat Commun. 2015 Oct 22;6:8687. doi: 10.1038/ncomms9687.

Abstract

Single-cell RNA-sequencing (scRNA-seq) facilitates identification of new cell types and gene regulatory networks as well as dissection of the kinetics of gene expression and patterns of allele-specific expression. However, to facilitate such analyses, separating biological variability from the high level of technical noise that affects scRNA-seq protocols is vital. Here we describe and validate a generative statistical model that accurately quantifies technical noise with the help of external RNA spike-ins. Applying our approach to investigate stochastic allele-specific expression in individual cells, we demonstrate that a large fraction of stochastic allele-specific expression can be explained by technical noise, especially for lowly and moderately expressed genes: we predict that only 17.8% of stochastic allele-specific expression patterns are attributable to biological noise with the remainder due to technical noise.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Alleles*
  • Animals
  • Artifacts*
  • Gene Expression Profiling / methods
  • Gene Regulatory Networks
  • Mice
  • Mouse Embryonic Stem Cells
  • RNA / genetics*
  • Sequence Analysis, RNA / methods*
  • Single-Cell Analysis / methods*
  • Stochastic Processes

Substances

  • RNA