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Revealing dynamics of gene expression variability in cell state space.

Dominic Grün
Published in: Nature methods (2019)
To decipher cell state transitions from single-cell transcriptomes it is crucial to quantify weak expression of lineage-determining factors, which requires computational methods that are sensitive to the variability of weakly expressed genes. Here, I introduce VarID, a computational method that identifies locally homogenous neighborhoods in cell state space, permitting the quantification of local variability in gene expression. VarID delineates neighborhoods with differential gene expression variability and reveals pseudo-temporal dynamics of variability during differentiation.
Keyphrases
  • single cell
  • gene expression
  • rna seq
  • dna methylation
  • cell therapy
  • genome wide
  • stem cells
  • binding protein
  • genome wide identification