Improving the value of public RNA-seq expression data by phenotype prediction

Nucleic Acids Research

Volumn 46, Issue 9, 2018, Pages

  Ellis, Shannon E ^a,b   Collado Torres, Leonardo ^b,c   Jaffe, Andrew ^a,b,c   Leek, Jeffrey T ^a,b  

^a JOHNS HOPKINS BLOOMBERG SCHOOL OF PUBLIC HEALTH   (United States)

^b JOHNS HOPKINS UNIVERSITY   (United States)

^c Lieber Institute for Brain Development Johns Hopkins Medical Campus   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; ARTICLE; CONTROLLED STUDY; CORRELATIONAL STUDY; FEMALE; GENE EXPRESSION; GENETIC ASSOCIATION; GENOMICS; HUMAN; HUMAN TISSUE; MALE; MIDDLE AGED; PHENOTYPE; PREDICTION; PRIORITY JOURNAL; RNA SEQUENCE; SENSITIVITY AND SPECIFICITY; SEQUENCE ANALYSIS; SEX CHROMOSOME; COMPUTER SIMULATION; GENE EXPRESSION PROFILING; SOFTWARE;

COMPUTER SIMULATION; FEMALE; GENE EXPRESSION PROFILING; HUMANS; MALE; PHENOTYPE; SEQUENCE ANALYSIS, RNA; SOFTWARE;

EID: 85061812937     PISSN: 03051048     EISSN: 13624962     Source Type: Journal    
DOI: 10.1093/nar/gky102     Document Type: Article

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