Accurately and comprehensively mapping millions of relatively short reads to a reference genome sequence can require not only specialized software, but also more structured and automated procedures to manage, analyze, and visualize the data. Additionally, the computational hardware required to efficiently process and store the data can be a necessary and often-overlooked component of a research plan.
Researchers at the University of Missouri Informatics Research Core discuss several aspects of the computational analysis of RNA-Seq, including file management and data quality control, analysis, and visualization. They provide a framework for a standard nomenclature system that can facilitate automation and the ability to track data provenance.
Additionally, they provide a general workflow of the computational analysis of RNA-Aeq and a downloadable package of scripts to automate the processing available at:
- Givan SA, Bottoms CA, Spollen WG. (2012) Computational Analysis of RNA-seq. Methods Mol Biol 883, 201-19. [abstract]