Validation of noise models for single-cell transcriptomics

ABSTRACT: Single-cell transcriptomics has recently emerged as a powerful technology to explore gene expression heterogeneity amongst 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 and after validation by single-molecule FISH experiments, we apply these models to demonstrate that growing mES cells in 2i instead of serum/LIF globally reduces gene expression variability.

ORGANISM(S): Mus musculus

PROVIDER: GSE54695 | GEO | 2014/04/20

SECONDARY ACCESSION(S): PRJNA237439

REPOSITORIES: GEO