@article {Bourgey459552,
	author = {Bourgey, Mathieu and Dali, Rola and Eveleigh, Robert and Chen, Kuang Chung and Letourneau, Louis and Fillon, Joel and Michaud, Marc and Caron, Maxime and Sandoval, Johanna and Lefebvre, Francois and Leveque, Gary and Mercier, Eloi and Bujold, David and Marquis, Pascale and Van, Patrick Tran and Morais, David and Tremblay, Julien and Shao, Xiaojian and Henrion, Edouard and Gonzalez, Emmanuel and Quirion, Pierre-Olivier and Caron, Bryan and Bourque, Guillaume},
	title = {GenPipes: an open-source framework for distributed and scalable genomic analyses},
	elocation-id = {459552},
	year = {2018},
	doi = {10.1101/459552},
	publisher = {Cold Spring Harbor Laboratory},
	abstract = {With the decreasing cost of sequencing and the rapid developments in genomics technologies and protocols, the need for validated bioinformatics software that enables efficient large-scale data processing is growing. Here we present GenPipes, a flexible Python-based framework that facilitates the development and deployment of multi-step workflows optimized for High Performance Computing clusters and the cloud. GenPipes already implements 12 validated and scalable pipelines for various genomics applications, including RNA-Seq, ChIP-Seq, DNA-Seq, Methyl-Seq, Hi-C, capture Hi-C, metagenomics and PacBio long read assembly. The software is available under a GPLv3 open-source license and is continuously updated to follow recent advances in genomics and bioinformatics. The framework has been already configured on several servers and a docker image is also available to facilitate additional installations. In summary, GenPipes offers genomic researchers a simple method to analyze different types of data, customizable to their needs and resources, as well as the flexibility to create their own workflows.},
	URL = {https://www.biorxiv.org/content/early/2018/11/01/459552},
	eprint = {https://www.biorxiv.org/content/early/2018/11/01/459552.full.pdf},
	journal = {bioRxiv}
}