Bayesian model selection reveals biological origins of zero inflation in single-cell transcriptomics

Bayesian model selection reveals biological origins of zero inflation in single-cell transcriptomics

Abstract Background Single-cell RNA sequencing is a powerful tool for characterizing cellular heterogeneity in gene expression. However, high variability and a large number of zero counts present challenges for analysis and interpretation. There is substantial controversy over the origins and proper...

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Bibliographic Details
Main Authors: Kwangbom Choi, Yang Chen, Daniel A. Skelly, Gary A. Churchill
Format: Article
Language:English
Published: BMC 2020-07-01
Series:Genome Biology
Subjects:
Single-cell RNA sequencing
Zero inflation
Bayesian model selection
Cell heterogeneity
Gene expression stochasticity
Online Access:http://link.springer.com/article/10.1186/s13059-020-02103-2

Internet

http://link.springer.com/article/10.1186/s13059-020-02103-2

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