MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data

Single-cell transcriptomics reveals gene expression heterogeneity but suffers from stochastic dropout and characteristic bimodal expression distributions in which expression is either strongly non-zero or non-detectable. We propose a two-part, generalized linear model for such bimodal data that para...

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Gepubliceerd in:Genome Biol
Hoofdauteurs: Finak, Greg, McDavid, Andrew, Yajima, Masanao, Deng, Jingyuan, Gersuk, Vivian, Shalek, Alex K., Slichter, Chloe K., Miller, Hannah W., McElrath, M. Juliana, Prlic, Martin, Linsley, Peter S., Gottardo, Raphael
Formaat: Artigo
Taal:Inglês
Gepubliceerd in: BioMed Central 2015
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Online toegang:https://ncbi.nlm.nih.gov/pmc/articles/PMC4676162/
https://ncbi.nlm.nih.gov/pubmed/26653891
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s13059-015-0844-5
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