MultiPLIER: A Transfer Learning Framework for Transcriptomics Reveals Systemic Features of Rare Disease

Cell Systems

Volumn 8, Issue 5, 2019, Pages 380-394.e4

  Taroni, Jaclyn N ^a,b   Grayson, Peter C ^c   Hu, Qiwen ^a   Eddy, Sean ^d   Kretzler, Matthias ^d,e   Merkel, Peter A ^a   Greene, Casey S ^a,b,f  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

^b Philadelphia   (United States)

^c NATIONAL INSTITUTE OF ARTHRITIS AND MUSCULOSKELETAL AND SKIN DISEASES   (United States)

^d UNIVERSITY OF MICHIGAN MEDICAL SCHOOL   (United States)

^e UNIVERSITY OF MICHIGAN HEALTH SYSTEM   (United States)

^f UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

genomics; machine learning; medulloblastoma; rare diseases; transcriptomics; transfer learning; unsupervised learning; vasculitis

Indexed keywords

GAMMA INTERFERON; TRANSCRIPTOME;

ALLERGIC RHINITIS; ANCA ASSOCIATED VASCULITIS; ARTICLE; CD4+ T LYMPHOCYTE; CELL DIFFERENTIATION; CELL PROLIFERATION; CHURG STRAUSS SYNDROME; DISEASE ACTIVITY; GENE EXPRESSION; GENE EXPRESSION PROFILING; GENOMICS; HUMAN; HUMAN TISSUE; MACHINE LEARNING; MEDULLOBLASTOMA; NATURAL KILLER CELL; NEPHROTIC SYNDROME; PERIPHERAL BLOOD MONONUCLEAR CELL; PRINCIPAL COMPONENT ANALYSIS; RARE DISEASE; RNA SEQUENCE; SARCOIDOSIS; SLEDAI; SYSTEMIC LUPUS ERYTHEMATOSUS; TRANSCRIPTOMICS; TRANSFER OF LEARNING; TUMOR ASSOCIATED LEUKOCYTE; TYPE I INTERFERON SIGNALING; TYPE II INTERFERON SIGNALING; WEGENER GRANULOMATOSIS; BIOLOGY; GENETICS; PROCEDURES; UNSUPERVISED MACHINE LEARNING;

COMPUTATIONAL BIOLOGY; GENE EXPRESSION PROFILING; HUMANS; MACHINE LEARNING; RARE DISEASES; TRANSCRIPTOME; UNSUPERVISED MACHINE LEARNING;

EID: 85065538871     PISSN: 24054712     EISSN: 24054720     Source Type: Journal    
DOI: 10.1016/j.cels.2019.04.003     Document Type: Article

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