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A complete tool set for molecular QTL discovery and analysis.

  • Delaneau O Department of Genetic Medicine and Development, University of Geneva, 1 Michel Servet, Geneva CH1211, Switzerland.
  • Ongen H Department of Genetic Medicine and Development, University of Geneva, 1 Michel Servet, Geneva CH1211, Switzerland.
  • Brown AA Department of Genetic Medicine and Development, University of Geneva, 1 Michel Servet, Geneva CH1211, Switzerland.
  • Fort A Department of Genetic Medicine and Development, University of Geneva, 1 Michel Servet, Geneva CH1211, Switzerland.
  • Panousis NI Department of Genetic Medicine and Development, University of Geneva, 1 Michel Servet, Geneva CH1211, Switzerland.
  • Dermitzakis ET Department of Genetic Medicine and Development, University of Geneva, 1 Michel Servet, Geneva CH1211, Switzerland.
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  • 2017-05-19
Published in:
  • Nature communications. - 2017
Algorithms
Chromosome Mapping
Genome, Human
Genome-Wide Association Study
Genotype
High-Throughput Nucleotide Sequencing
Humans
Phenotype
Polymorphism, Single Nucleotide
Quality Control
Quantitative Trait Loci
English 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/.
Language
  • English
Open access status
gold
Identifiers
Persistent URL
https://sonar.ch/global/documents/170406
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