Journal
NATURE METHODS
Volume 10, Issue 11, Pages 1093-1095Publisher
NATURE PORTFOLIO
DOI: 10.1038/NMETH.2645
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Funding
- European Union
- Australian Research Council
- European Research Council [260507]
- European Research Council (ERC) [260507] Funding Source: European Research Council (ERC)
- Biotechnology and Biological Sciences Research Council [1300642] Funding Source: researchfish
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Single-cell RNA-seq can yield valuable insights about the variability within a population of seemingly homogeneous cells. We developed a quantitative statistical method to distinguish true biological variability from the high levels of technical noise in single-cell experiments. Our approach quantifies the statistical significance of observed cell-to-cell variability in expression strength on a gene-by-gene basis. We validate our approach using two independent data sets from Arabidopsis thaliana and Mus musculus.
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