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

• Published in: Bioinformatics Vol. 32; no. 4; pp. 523 - 532
• Main Authors: Lewin, Alex, Saadi, Habib, Peters, James E, Moreno-Moral, Aida, Lee, James C, Smith, Kenneth G C, Petretto, Enrico, Bottolo, Leonardo, Richardson, Sylvia
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 15.02.2016
• Subjects: Algorithms; Animals; Bayes Theorem; Bayesian analysis; Bioinformatics; Diabetes Mellitus, Type 1 - genetics; Gene expression; Gene Expression Regulation; Gene Regulatory Networks; Genes; Genomics - methods; Hot spots; Humans; Inflammation - genetics; Inflammatory Bowel Diseases - genetics; Mathematical models; Models, Theoretical; Organ Specificity; Original Papers; Polymorphism, Single Nucleotide - genetics; Programming Languages; Quantitative Trait Loci - genetics; Rats; Searching; Software; Source code; Tissue Distribution

Analysing the joint association between a large set of responses and predictors is a fundamental statistical task in integrative genomics, exemplified by numerous expression Quantitative Trait Loci (eQTL) studies. Of particular interest are the so-called ': hotspots ': , important genetic...