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A complete tool set for molecular QTL discovery and analysis

Author

Listed:
  • Olivier Delaneau

    (University of Geneva
    Swiss Institute of Bioinformatics, University of Geneva
    Institute of Genetics and Genomics in Geneva, University of Geneva)

  • Halit Ongen

    (University of Geneva
    Swiss Institute of Bioinformatics, University of Geneva
    Institute of Genetics and Genomics in Geneva, University of Geneva)

  • Andrew A. Brown

    (University of Geneva
    Swiss Institute of Bioinformatics, University of Geneva
    Institute of Genetics and Genomics in Geneva, University of Geneva)

  • Alexandre Fort

    (University of Geneva)

  • Nikolaos I. Panousis

    (University of Geneva
    Swiss Institute of Bioinformatics, University of Geneva
    Institute of Genetics and Genomics in Geneva, University of Geneva)

  • Emmanouil T. Dermitzakis

    (University of Geneva
    Swiss Institute of Bioinformatics, University of Geneva
    Institute of Genetics and Genomics in Geneva, University of Geneva)

Abstract

Population scale studies combining genetic information with molecular phenotypes (for example, gene expression) have become a standard to dissect the effects of genetic variants onto organismal phenotypes. These kinds of data sets require powerful, fast and versatile methods able to discover molecular Quantitative Trait Loci (molQTL). Here we propose such a solution, QTLtools, a modular framework that contains multiple new and well-established methods to prepare the data, to discover proximal and distal molQTLs and, finally, to integrate them with GWAS variants and functional annotations of the genome. We demonstrate its utility by performing a complete expression QTL study in a few easy-to-perform steps. QTLtools is open source and available at https://qtltools.github.io/qtltools/ .

Suggested Citation

  • Olivier Delaneau & Halit Ongen & Andrew A. Brown & Alexandre Fort & Nikolaos I. Panousis & Emmanouil T. Dermitzakis, 2017. "A complete tool set for molecular QTL discovery and analysis," Nature Communications, Nature, vol. 8(1), pages 1-7, August.
    • Handle: RePEc:nat:natcom:v:8:y:2017:i:1:d:10.1038_ncomms15452
    DOI: 10.1038/ncomms15452
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