Bayesian approach to single-cell differential expression analysis

Nature Methods

Volumn 11, Issue 7, 2014, Pages 740-742

  Kharchenko, Peter V ^a,b,c   Silberstein, Lev ^c,d,e   Scadden, David T ^c,d,e  

^a Harvard Medical School Center for Biomedical Informatics   (United States)

^b BOSTON CHILDREN S HOSPITAL   (United States)

^c HARVARD STEM CELL INSTITUTE   (United States)

^d MASSACHUSETTS GENERAL HOSPITAL CANCER CENTER   (United States)

^e Harvard University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; BAYES THEOREM; CELL POPULATION; CELL SUBPOPULATION; CORRELATIONAL STUDY; CYTOMETRY; EMBRYO; EMBRYONIC STEM CELL; FIBROBLAST; GENE EXPRESSION; MOUSE; MOUSE EMBRYO; NOISE; NONHUMAN; OBSERVATIONAL STUDY; PRIORITY JOURNAL; QUANTITATIVE STUDY; RNA SEQUENCE; SINGLE CELL ANALYSIS;

ALGORITHMS; BAYES THEOREM; GENE EXPRESSION PROFILING; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; SEQUENCE ANALYSIS, RNA; SINGLE-CELL ANALYSIS;

EID: 84903574951     PISSN: 15487091     EISSN: 15487105     Source Type: Journal    
DOI: 10.1038/nmeth.2967     Document Type: Article

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