GenPipes: an open-source framework for distributed and scalable genomic analyses

Autor: Marc Michaud, Eloi Mercier, Mathieu Bourgey, Pierre-Olivier Quirion, Gary Leveque, Johanna Sandoval, Maxime Caron, Emmanuel Gonzalez, Joel Fillon, Julien Tremblay, Guillaume Bourque, Francois Lefebvre, Louis Letourneau, Patrick Tran Van, David Anderson de Lima Morais, Rola Dali, Xiaojian Shao, Edouard Henrion, Robert Eveleigh, B. Caron, Pascale Marquis, Kuang Chung Chen, David Bujold
Rok vydání: 2018
Předmět:
Zdroj: GigaScience
GigaScience, vol. 8, no. 6
ISSN: 2047-217X
Popis: Background 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. Findings 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 sequencing, chromatin immunoprecipitation sequencing, DNA sequencing, methylation sequencing, Hi-C, capture Hi-C, metagenomics, and Pacific Biosciences 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 already been configured on several servers, and a Docker image is also available to facilitate additional installations. Conclusions GenPipes offers genomics 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.
Databáze: OpenAIRE