| Abstract | 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. |
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