A discriminative learning approach to differential expression analysis for single-cell RNA-seq

Nature Methods

Volumn 16, Issue 2, 2019, Pages 163-166

  Ntranos, Vasilis ^a,b   Yi, Lynn ^c,d   Melsted, Páll ^e   Pachter, Lior ^d,f  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b Stanford University   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

^d California Institute of Technology   (United States)

^e UNIVERSITY OF ICELAND   (Iceland)

^f California Institute of Technology   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CD45RA ANTIGEN; RECEPTOR TYPE TYROSINE PROTEIN PHOSPHATASE C; RNA; ISOPROTEIN; TRANSCRIPTOME;

3' UNTRANSLATED REGION; ARTICLE; CONTROLLED STUDY; CYTOTOXIC T LYMPHOCYTE; DISCRIMINATION LEARNING; GENE EXPRESSION; HELPER CELL; HUMAN; HUMAN CELL; MYOBLAST; PERIPHERAL BLOOD MONONUCLEAR CELL; PRIORITY JOURNAL; RNA SEQUENCE; SINGLE CELL ANALYSIS; T LYMPHOCYTE; ALGORITHM; COMPUTER SIMULATION; CYTOLOGY; DEVICES; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; GENETIC DATABASE; GENETIC MARKER; GENETICS; MONONUCLEAR CELL; PROCEDURES; REGRESSION ANALYSIS; SEQUENCE ANALYSIS; SOFTWARE;

ALGORITHMS; COMPUTER SIMULATION; DATABASES, GENETIC; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; GENETIC MARKERS; HUMANS; LEUKOCYTES, MONONUCLEAR; PROTEIN ISOFORMS; REGRESSION ANALYSIS; RNA; SEQUENCE ANALYSIS, RNA; SINGLE-CELL ANALYSIS; SOFTWARE; T-LYMPHOCYTES, CYTOTOXIC; TRANSCRIPTOME;

EID: 85060474248     PISSN: 15487091     EISSN: 15487105     Source Type: Journal    
DOI: 10.1038/s41592-018-0303-9     Document Type: Article

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