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Implementation of a Reproducible, Accessible and Transparent RNA-seq Bioinformatics Pipeline within the Galaxy Platform

Abstract

Thahmina Ali, Baekdoo Kim, Carlos Lijeron, Changsu Dong, Claudia Wultsch, and Konstantinos Krampis

The technology of RNA sequencing (RNA-seq) has not only proven powerful in transcriptome studies but has become a key approach in translational medicine. In this work, we present a reusable and reproducible bioinformatics pipeline for processing and analyzing RNA-seq data, implemented as an automated workflow within the open-source, web-based Galaxy web platform. With this workflow, researchers with little to no training in computer programming or bioinformatics experience can perform routine, high quality RNA-seq analysis, and generate intuitive results. We evaluated our implementation approach of the RNA-Seq pipeline using cancer transcriptome data, demonstrating that it is well positioned for clinical applications providing a set of advantages over existing methods.

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