Source: fastqtl Maintainer: Debian Med Packaging Team Uploaders: Dylan Aïssi Section: science Priority: optional Build-Depends: debhelper-compat (= 13), dh-python, python3, libboost-dev, libboost-iostreams-dev, libboost-program-options-dev, libgsl-dev, r-mathlib, zlib1g-dev, libblas-dev, libeigen3-dev, libhts-dev, libbz2-dev Standards-Version: 4.6.1 Vcs-Browser: https://salsa.debian.org/med-team/fastqtl Vcs-Git: https://salsa.debian.org/med-team/fastqtl.git Homepage: http://fastqtl.sourceforge.net/ Rules-Requires-Root: no Package: fastqtl Architecture: any Depends: ${shlibs:Depends}, ${misc:Depends}, ${python3:Depends}, python3, ${misc:Depends} Recommends: r-cran-qvalue, r-cran-tools, r-cran-argparser Suggests: fastqtl-doc Description: Quantitative Trait Loci (QTL) mapper in cis for molecular phenotypes The goal of FastQTL is to identify single-nucleotide polymorphisms (SNPs) which are significantly associated with various molecular phenotypes (i.e. expression of known genes, cytosine methylation levels, etc). It performs scans for all possible phenotype-variant pairs in cis (i.e. variants located within a specific window around a phenotype). FastQTL implements a new permutation scheme (Beta approximation) to accurately and rapidly correct for multiple-testing at both the genotype and phenotype levels. Package: fastqtl-doc Architecture: all Multi-Arch: foreign Section: doc Depends: ${misc:Depends} Enhances: fastqtl Description: QTL mapper in cis for molecular phenotypes - documentation The goal of FastQTL is to identify single-nucleotide polymorphisms (SNPs) which are significantly associated with various molecular phenotypes (i.e. expression of known genes, cytosine methylation levels, etc). It performs scans for all possible phenotype-variant pairs in cis (i.e. variants located within a specific window around a phenotype). FastQTL implements a new permutation scheme (Beta approximation) to accurately and rapidly correct for multiple-testing at both the genotype and phenotype levels. . This package provides documentation and example data to work with FastQTL.