Computational assignment of cell-cycle stage from single-cell transcriptome data

Methods

Volumn 85, Issue , 2015, Pages 54-61

  Scialdone, Antonio ^a,b   Natarajan, Kedar N ^a,b   Saraiva, Luis R ^a,b   Proserpio, Valentina ^a,b   Teichmann, Sarah A ^a,b   Stegle, Oliver ^b   Marioni, John C ^a,b   Buettner, Florian ^b,c  

^a WELLCOME TRUST SANGER INSTITUTE   (United Kingdom)

^b EUROPEAN BIOINFORMATICS INSTITUTE   (United Kingdom)

^c INSTITUTE OF EPIDEMIOLOGY   (Germany)

Author keywords

Cell cycle; Computational biology; Machine learning; Single cell RNA seq

Indexed keywords

ARTICLE; BLASTOMA; CELL CYCLE G1 PHASE; CELL CYCLE G2 PHASE; CELL CYCLE PHASE; CELL CYCLE S PHASE; CLASSIFIER; HUMAN; LIVER CELL; MACHINE LEARNING; NONHUMAN; PREDICTION; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; RANDOM FOREST; RNA SEQUENCE; SUPPORT VECTOR MACHINE; T LYMPHOCYTE; TRANSCRIPTOMICS; ANIMAL; BIOLOGY; CELL CYCLE; EMBRYONIC STEM CELL; GENE EXPRESSION PROFILING; MOUSE; PHYSIOLOGY; PROCEDURES; SINGLE CELL ANALYSIS; TUMOR CELL LINE;

TRANSCRIPTOME;

ANIMALS; CELL CYCLE; CELL LINE, TUMOR; COMPUTATIONAL BIOLOGY; EMBRYONIC STEM CELLS; GENE EXPRESSION PROFILING; HEPATOCYTES; HUMANS; MACHINE LEARNING; MICE; SINGLE-CELL ANALYSIS; TRANSCRIPTOME;

EID: 84939772971     PISSN: 10462023     EISSN: 10959130     Source Type: Journal    
DOI: 10.1016/j.ymeth.2015.06.021     Document Type: Article

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