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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...
Autores principales: | 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 |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4676162/ https://www.ncbi.nlm.nih.gov/pubmed/26653891 http://dx.doi.org/10.1186/s13059-015-0844-5 |
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