MT-HESS

The software tool MT-HESS is designed for integrative genomics, specifically for analyzing the joint association between a large set of responses and predictors, such as SNPs and gene expression in multiple tissues, cells, or conditions. The tool uses a Bayesian hierarchical model that goes beyond one-at-a-time association tests and uses a fully multivariate model search across all linear combinations of SNPs, coupled with a model of the correlation between condition/tissue-specific responses. The tool also leverages shared information across different genes to improve hotspot detection.

Topic

Gene expression;Omics;Genetics

Detail

  • Operation: Modelling and simulation

  • Software interface: Command-line user interface

  • Language: C++

  • License: -

  • Cost: Free

  • Version name: 0.3

  • Credit: Medical Research Council, a Wellcome Trust Clinical PhD Programme Fellowship, Wellcome Trust Grant, British Heart Foundation PhD Studentship Grant, Engineering and Physical Sciences Research Council Grant.

  • Input: -

  • Output: -

  • Contact: sylvia.richardson@mrc-bsu.cam.ac.uk;lb664@cam.ac.uk

  • Collection: -

  • Maturity: -

Publications

  • MT-HESS: an efficient Bayesian approach for simultaneous association detection in OMICS datasets, with application to eQTL mapping in multiple tissues.
  • Lewin A, et al. MT-HESS: an efficient Bayesian approach for simultaneous association detection in OMICS datasets, with application to eQTL mapping in multiple tissues. MT-HESS: an efficient Bayesian approach for simultaneous association detection in OMICS datasets, with application to eQTL mapping in multiple tissues. 2016; 32:523-32. doi: 10.1093/bioinformatics/btv568
  • https://doi.org/10.1093/bioinformatics/btv568
  • PMID: 26504141
  • PMC: PMC4743623

Download and documentation

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