henhaobio
Sign in

bioRxivBioinformatics

Fast and efficient QTL mapper for thousands of molecular phenotypes

Halit OngeniD, Alfonso BuiliD, Andrew BrowniD, Emmanouil Dermitzakis, Olivier DelaneauiD

PDFDOIPreprintCode

Abstract

MotivationIn 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.\n\nResultsWe 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.\n\nAvailabilitySource code, binaries and comprehensive documentation of FastQTL are freely available to download at http://fastqtl.sourceforge.net/.\n\nContactolivier.delaneau@unige.ch

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISGao '21Mondal '25Zhou '25Corty '18Broman '18Delaneau '17
72% semantic matchBioinformatics
Xingjian Gao, Jiarui Li, Xinxuan Liu+4 more·bioRxiv·Nov 16, 2021· 1 citations