dc.contributor.author | Finak, Greg | |
dc.contributor.author | McDavid, Andrew | |
dc.contributor.author | Yajima, Masanao | |
dc.contributor.author | Deng, Jingyuan | |
dc.contributor.author | Gersuk, Vivian | |
dc.contributor.author | Prlic, Martin | |
dc.contributor.author | Gottardo, Raphael | |
dc.contributor.author | Slichter, Chloe K. | |
dc.contributor.author | Miller, Hannah W. | |
dc.contributor.author | McElrath, M. Juliana | |
dc.contributor.author | Linsley, Peter S. | |
dc.contributor.author | Shalek, Alex | |
dc.date.accessioned | 2015-12-21T17:40:51Z | |
dc.date.available | 2015-12-21T17:40:51Z | |
dc.date.issued | 2015-12 | |
dc.date.submitted | 2015-07 | |
dc.identifier.issn | 1474-760X | |
dc.identifier.uri | http://hdl.handle.net/1721.1/100458 | |
dc.description.abstract | 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 parameterizes both of these features. We argue that the cellular detection rate, the fraction of genes expressed in a cell, should be adjusted for as a source of nuisance variation. Our model provides gene set enrichment analysis tailored to single-cell data. It provides insights into how networks of co-expressed genes evolve across an experimental treatment. MAST is available at https://github.com/RGLab/MAST. | en_US |
dc.publisher | BioMed Central | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1186/s13059-015-0844-5 | en_US |
dc.title | MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data | en_US |
dc.type | Article | en_US |
dc.identifier.citation | Finak, Greg, et al. "MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data." Genome Biology. 2015 Dec 10;16(1):278. | en_US |
dc.contributor.department | Institute for Medical Engineering and Science | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Chemistry | en_US |
dc.contributor.mitauthor | Shalek, Alex | en_US |
dc.relation.journal | Genome Biology | en_US |
dc.eprint.version | Final published version | en_US |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
dc.date.updated | 2015-12-11T04:55:39Z | |
dc.language.rfc3066 | en | |
dc.rights.holder | Finak et al. | |
dspace.orderedauthors | 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 | en_US |
mit.license | OPEN_ACCESS_POLICY | en_US |
mit.metadata.status | Complete | |