Population scale studies combining genetic information with molecular phenotypes (e.g. gene expression) become a standard to dissect the effects of genetic variants onto organismal phenotypes. This kind of datasets requires 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 methods to prepare the data, to discover proximal and distal molQTLs and to finally 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 and easy-to-perform steps. QTLtools is open source and available at https://qtltools.github.io/qtltools/.