Interpretable dimensionality reduction of single cell transcriptome data with deep generative models

Nature Communications

Volumn 9, Issue 1, 2018, Pages

  Ding, Jiarui ^a,b,c   Condon, Anne ^a   Shah, Sohrab P ^a,b,d  

^a UNIVERSITY OF BRITISH COLUMBIA   (Canada)

^b BRITISH COLUMBIA CANCER AGENCY   (Canada)

^c BROAD INSTITUTE OF MIT AND HARVARD   (United States)

^d MEMORIAL SLOAN KETTERING CANCER CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

TRANSCRIPTOME; RNA;

ALGORITHM; CELL COMPONENT; GENE; GENE EXPRESSION; NUMERICAL MODEL; RNA; TWO-DIMENSIONAL MODELING;

ARTICLE; EMBEDDING; GENE EXPRESSION; HUMAN; HUMAN CELL; MOUSE; NOISE; NONHUMAN; RNA SEQUENCE; SINGLE CELL ANALYSIS; TRANSCRIPTOMICS; ALGORITHM; ANIMAL; CELLS; CHEMISTRY; GENETICS; METABOLISM; NUCLEIC ACID DATABASE; SEQUENCE ANALYSIS; SOFTWARE; STATISTICAL MODEL;

ALGORITHMS; ANIMALS; CELLS; DATABASES, NUCLEIC ACID; HUMANS; MICE; MODELS, STATISTICAL; RNA; SEQUENCE ANALYSIS, RNA; SINGLE-CELL ANALYSIS; SOFTWARE; TRANSCRIPTOME;

EID: 85047423831     PISSN: None     EISSN: 20411723     Source Type: Journal    
DOI: 10.1038/s41467-018-04368-5     Document Type: Article

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