TOGGLe, a flexible framework for easily building complex workflows and performing robust large-scale NGS analyses

Tranchant-Dubreuil, C.; Ravel, S.; Monat, C.; Sarah, G.; Diallo, A.; Helou, L.; Dereeper, A.; Tando, N.; Orjuela-Bouniol, J.; Sabot, F.

doi:10.1101/245480

bioRxiv · 10.1101/245480

TOGGLe, a flexible framework for easily building complex workflows and performing robust large-scale NGS analyses

Tranchant-Dubreuil, C.·Ravel, S.·Monat, C.·Sarah, G.·Diallo, A.·Helou, L.·Dereeper, A.·Tando, N.·Orjuela-Bouniol, J.·Sabot, F.

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Abstract

The advent of NGS has intensified the need for robust pipelines to perform high-performance automated analyses. The required softwares depend on the sequencing method used to produce raw data (e.g. Whole genome sequencing, Genotyping By Sequencing, RNASeq) as well as the kind of analyses to carry on (GWAS, population structure, differential expression). These tools have to be generic and scalable, and should meet the biologists needs.\n\nHere, we present the new version of TOGGLe (Toolbox for Generic NGS Analyses), a simple and highly flexible framework to easily and quickly generate pipelines for large-scale second-and third-generation sequencing analyses, including multi-threading support. TOGGLe comprises a workflow manager designed to be as effortless as possible to use for biologists, so the focus can remain on the analyses. Embedded pipelines are easily customizable and supported analyses are reproducible and shareable. TOGGLe is designed as a generic, adaptable and fast evolutive solution, and has been tested and used in large-scale projects with numerous samples and organisms. It is freely available at http://toggle.southgreen.fr/ under the GNU GPLv3/CeCill-C licenses) and can be deployed onto HPC clusters as well as on local machines.

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Tranchant-Dubreuil, C., Ravel, S., Monat, C., Sarah, G., Diallo, A., Helou, L., Dereeper, A., Tando, N., Orjuela-Bouniol, J., Sabot, F.. 2018-01-10. TOGGLe, a flexible framework for easily building complex workflows and performing robust large-scale NGS analyses. https://doi.org/10.1101/245480

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