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Revealing Dynamics of Gene Expression Variability in Cell State Space
To decipher cell state transitions from single-cell transcriptomes it is crucial to quantify weak expression of lineage determining factors, requiring computational methods sensitive to variability of lowly expressed genes. We here introduce VarID, a computational method that identifies locally homo...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6949127/ https://www.ncbi.nlm.nih.gov/pubmed/31740822 http://dx.doi.org/10.1038/s41592-019-0632-3 |
Sumario: | To decipher cell state transitions from single-cell transcriptomes it is crucial to quantify weak expression of lineage determining factors, requiring computational methods sensitive to variability of lowly expressed genes. We here introduce VarID, a computational method that identifies locally homogenous neighborhoods in cell state space, permitting the quantification of local gene expression variability. VarID delineates neighborhoods with differential gene expression variability and reveals pseudo-temporal dynamics of variability during differentiation. |
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