Validation of noise models for single-cell transcriptomics.
Nat Methods, 2014/6;11(6):637-40.
Grün D[1], Kester L[1], van Oudenaarden A[2]
Affiliations
PMID: 24747814DOI: 10.1038/nmeth.2930
Impact factor: 47.99
Abstract
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.
MeSH terms
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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