Validation of noise models for single-cell transcriptomics

Dominic Grün, Lennart Kester, Alexander van Oudenaarden

Research output: Contribution to journal/periodicalArticleScientificpeer-review

474 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)637-40
Number of pages4
JournalNature Methods
Issue number6
Publication statusPublished - Jun 2014


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


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