EBSeq-HMM: A Bayesian approach for identifying gene-expression changes in ordered RNA-seq experiments

Bioinformatics

Volumn 31, Issue 16, 2015, Pages 2614-2622

  Leng, Ning ^a,b   Li, Yuan ^a   McIntosh, Brian E ^b   Nguyen, Bao Kim ^b   Duffin, Bret ^b   Tian, Shulan ^b   Thomson, James A ^b,c,d   Dewey, Colin N ^c   Stewart, Ron ^b   Kendziorski, Christina ^c  

^a University of Wisconsin Madison   (United States)

^b MORGRIDGE INSTITUTE FOR RESEARCH   (United States)

^c UNIVERSITY OF WISCONSIN SCHOOL OF MEDICINE AND PUBLIC HEALTH   (United States)

^d UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BAYES THEOREM; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; HIGH THROUGHPUT SEQUENCING; HUMAN; PROCEDURES; SEQUENCE ANALYSIS; SOFTWARE;

BAYES THEOREM; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS; SEQUENCE ANALYSIS, RNA; SOFTWARE;

EID: 84939501639     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btv193     Document Type: Article

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