Validation of noise models for single-cell transcriptomics

Nat Methods. 2014 Jun;11(6):637-40. doi: 10.1038/nmeth.2930. Epub 2014 Apr 20.


Single-cell transcriptomics has recently emerged as a powerful technology to explore gene expression heterogeneity among single cells. Here we identify two major sources of technical variability: sampling noise and global cell-to-cell variation in sequencing efficiency. We propose noise models to correct for this, which we validate using single-molecule FISH. We demonstrate that gene expression variability in mouse embryonic stem cells depends on the culture condition.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Embryonic Stem Cells / metabolism
  • Gene Expression Profiling / methods*
  • Gene Expression Profiling / standards*
  • Gene Expression Regulation*
  • Mice
  • Models, Biological*
  • Observer Variation
  • Selection Bias
  • Sequence Analysis, RNA
  • Signal-To-Noise Ratio*
  • Transcription Factors / metabolism


  • Transcription Factors

Associated data

  • GEO/GSE54695