Fast and efficient QTL mapper for thousands of molecular phenotypes

Halit Ongen, Alfonso Buil, Andrew Anand Brown, Emmanouil T. Dermitzakis (Lead / Corresponding author), Olivier Delaneau (Lead / Corresponding author)

Research output: Contribution to journalArticle

94 Citations (Scopus)
128 Downloads (Pure)

Abstract

MOTIVATION: In order to discover quantitative trait loci, multi-dimensional genomic datasets combining DNA-seq and ChiP-/RNA-seq require methods that rapidly correlate tens of thousands of molecular phenotypes with millions of genetic variants while appropriately controlling for multiple testing.

RESULTS: We have developed FastQTL, a method that implements a popular cis-QTL mapping strategy in a user- and cluster-friendly tool. FastQTL also proposes an efficient permutation procedure to control for multiple testing. The outcome of permutations is modeled using beta distributions trained from a few permutations and from which adjusted P-values can be estimated at any level of significance with little computational cost. The Geuvadis & GTEx pilot datasets can be now easily analyzed an order of magnitude faster than previous approaches.

AVAILABILITY AND IMPLEMENTATION: Source code, binaries and comprehensive documentation of FastQTL are freely available to download at http://fastqtl.sourceforge.net/

CONTACT: emmanouil.dermitzakis@unige.ch or olivier.delaneau@unige.ch

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Original languageEnglish
Pages (from-to)1479-1485
Number of pages7
JournalBioinformatics
Volume32
Issue number10
Early online date26 Dec 2015
DOIs
Publication statusPublished - 15 May 2016

Keywords

  • Genomics
  • Phenotype
  • Quantitative Trait Loci
  • Software
  • Statistical Distributions

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