Fast and efficient QTL mapper for thousands of molecular phenotypes

By Halit Ongen, A. Buil, Andrew Anand Brown, Emmanouil T. Dermitzakis, Olivier Delaneau. bioRxiv, 2015

536 citations recorded by the source corpus.

Motivation In order to discover quantitative trait loci (QTLs), multi-dimensional genomic data sets 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 data sets can be now easily analyzed an order of magnitude faster than previous approaches. Availability Source code, binaries and comprehensive documentation of FastQTL are freely available to download at http://fastqtl.sourceforge.net/. Contact olivier.delaneau@unige.ch

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/f0f9da69867fbe4545464cf98f015df8d3987754

Citations in the corpus

• Annotation-free quantification of RNA splicing using LeafCutter (2017, unknown): “We used the proportion of reads supporting each alternatively excised intron identified by LeafCutter and a linear model 30 to map sQTLs (Supplementary Note).”