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Fast and efficient QTL mapper for thousands of molecular phenotypes

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. Re...

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Detalles Bibliográficos
Autores principales: Ongen, Halit, Buil, Alfonso, Brown, Andrew Anand, Dermitzakis, Emmanouil T., Delaneau, Olivier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4866519/
https://www.ncbi.nlm.nih.gov/pubmed/26708335
http://dx.doi.org/10.1093/bioinformatics/btv722
Descripción
Sumario: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.