Flowr: Robust and efficient pipelines using a simple language-agnostic approach

BioRxiv : the Preprint Server for Biology
Sahil SethJianhua Zhang

Abstract

Motivation: Bioinformatics analyses have become increasingly intensive computing processes, with lowering costs and increasing numbers of samples. Each laboratory spends time creating and maintaining a set of pipelines, which may not be robust, scalable, or efficient. Further, the existence of different computing environments across institutions hinders both collabo-ration and the portability of analysis pipelines. Results: Flowr is a robust and scalable framework for designing and deploying computing pipelines in an easy-to-use fashion. It implements a scatter-gather approach using computing clusters, simplifying the concept to the use of five simple terms (in submission and dependency types). Most importantly, it is flexible, such that customizing existing pipelines is easy, and since it works across several computing environments (LSF, SGE, Torque, and SLURM), it is portable. Availability: http://docs.flowr.space

Related Concepts

Environment
Bio-Informatics
Laboratory
TFCP2
Analysis
Motivation

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