Format

Send to

Choose Destination
Nat Commun. 2017 May 18;8:15452. doi: 10.1038/ncomms15452.

A complete tool set for molecular QTL discovery and analysis.

Author information

1
Department of Genetic Medicine and Development, University of Geneva, 1 Michel Servet, Geneva CH1211, Switzerland.
2
Swiss Institute of Bioinformatics, University of Geneva, 1 Michel Servet, Geneva CH1211, Switzerland.
3
Institute of Genetics and Genomics in Geneva, University of Geneva, 1 Michel Servet, Geneva CH1211, Switzerland.

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/.

PMID:
28516912
PMCID:
PMC5454369
DOI:
10.1038/ncomms15452
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Nature Publishing Group Icon for PubMed Central
Loading ...
Support Center