Abstract
Background RNA sequencing (RNA-seq) is a widely used technique in many scientific studies. Given the plethora of models and software packages that have been developed for processing and analyzing RNA-seq datasets, choosing the most appropriate ones is a time-consuming process that requires an in-depth understanding of the data, as well as of the principles and parameters of each tool. In addition, packages designed for individual tasks are developed in different programming languages and have dependencies of various degrees of complexity, which renders their installation and execution challenging for users with limited computational expertise. Workflow languages and execution engines with support for virtualization and encapsulation options such as containers and Conda environments facilitate these tasks considerably. The resulting computational workflows can then be reliably shared with the scientific community, enhancing reusability and the reproducibility of results as individual analysis steps are becoming more transparent and portable. Methods Here we present ZARP, a general purpose RNA-seq analysis workflow that builds on state-of-the-art software in the field to facilitate the analysis of RNA-seq datasets. ZARP is developed in the Snakemake workflow language and can run locally or in a cluster environment, generating extensive reports not only of the data but also of the options utilized. It is built using modern technologies with the ultimate goal to reduce the hands-on time for bioinformaticians and non-expert users and serve as a template for future workflow development. To this end, we also provide ZARP-cli, a dedicated command-line interface that may make running ZARP on an RNA-seq library of interest as easy as executing a single two-word command. Conclusions ZARP is a powerful RNA-seq analysis workflow that is easy to use even for beginners, built using best software development practices, available under a permissive Open Source license and open to contributions by the scientific community.
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