MT-HESS: An efficient Bayesian approach for simultaneous association detection in OMICS datasets, with application to eQTL mapping in multiple tissues

Bioinformatics

Volumn 32, Issue 4, 2016, Pages 523-532

  Lewin, Alex ^a   Saadi, Habib ^b   Peters, James E ^c,d   Moreno Moral, Aida ^b   Lee, James C ^c   Smith, Kenneth G C ^c   Petretto, Enrico ^b,e   Bottolo, Leonardo ^b,f   Richardson, Sylvia ^d  

^a BRUNEL UNIVERSITY   (United Kingdom)

^b IMPERIAL COLLEGE LONDON   (United Kingdom)

^c UNIVERSITY OF CAMBRIDGE   (United Kingdom)

^d UNIVERSITY OF CAMBRIDGE   (United Kingdom)

^e DUKE NUS MEDICAL SCHOOL   (Singapore)

^f UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ANIMAL; ANTIBODY SPECIFICITY; BAYES THEOREM; COMPUTER LANGUAGE; GENE EXPRESSION REGULATION; GENE REGULATORY NETWORK; GENETICS; GENOMICS; HUMAN; INFLAMMATION; INFLAMMATORY BOWEL DISEASE; INSULIN DEPENDENT DIABETES MELLITUS; PROCEDURES; QUANTITATIVE TRAIT LOCUS; RAT; SINGLE NUCLEOTIDE POLYMORPHISM; SOFTWARE; THEORETICAL MODEL; TISSUE DISTRIBUTION;

ALGORITHMS; ANIMALS; BAYES THEOREM; DIABETES MELLITUS, TYPE 1; GENE EXPRESSION REGULATION; GENE REGULATORY NETWORKS; GENOMICS; HUMANS; INFLAMMATION; INFLAMMATORY BOWEL DISEASES; MODELS, THEORETICAL; ORGAN SPECIFICITY; POLYMORPHISM, SINGLE NUCLEOTIDE; PROGRAMMING LANGUAGES; QUANTITATIVE TRAIT LOCI; RATS; SOFTWARE; TISSUE DISTRIBUTION;

EID: 84959860765     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btv568     Document Type: Article

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