Beyond comparisons of means: understanding changes in gene expression at the single-cell level

Catalina A Vallejos, Sylvia Richardson, John C Marioni

Research output: Contribution to journalArticlepeer-review

Abstract

Traditional differential expression tools are limited to detecting changes in overall expression, and fail to uncover the rich information provided by single-cell level data sets. We present a Bayesian hierarchical model that builds upon BASiCS to study changes that lie beyond comparisons of means, incorporating built-in normalization and quantifying technical artifacts by borrowing information from spike-in genes. Using a probabilistic approach, we highlight genes undergoing changes in cell-to-cell heterogeneity but whose overall expression remains unchanged. Control experiments validate our method’s performance and a case study suggests that novel biological insights can be revealed. Our method is implemented in R and available at https://github.com/catavallejos/BASiCS.

Original languageEnglish
Article number70
JournalGenome Biology
Volume17
DOIs
Publication statusPublished - 15 Apr 2016

Keywords

  • Animals
  • Bayes Theorem
  • Gene Expression Profiling/methods
  • Genetic Heterogeneity
  • Humans
  • Mice
  • Mouse Embryonic Stem Cells/cytology
  • Sequence Analysis, RNA/methods
  • Single-Cell Analysis/methods
  • Web Browser

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