RSEQtools: A modular framework to analyze RNA-Seq data using compact, anonymized data summaries


Summary: The advent of next-generation sequencing for functional genomics has given rise to quantities of sequence information that are often so large that they are difficult to handle. Moreover, sequence reads from a specific individual can contain sufficient information to potentially identify and genetically characterize that person, raising privacy concerns. In order to address these issues we have developed the Mapped Read Format (MRF), a compact data summary format for both short and long read alignments that enables the anonymization of confidential sequence information, while allowing one to still carry out many functional genomics studies. We have developed a suite of tools that use this format for the analysis of RNA-Seq experiments. RSEQtools consists of a set of modules that perform common tasks such as calculating gene expression values, generating signal tracks of mapped reads, and segmenting that signal into actively transcribed regions. Moreover, these tools can readily be used to build customizable RNA-Seq workflows. In addition to the anonymization afforded by this format it also facilitates the decoupling of the alignment of reads from downstream analyses.

Availability and implementation: RSEQtools is implemented in C and the source code is available at

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Lukas Habegger, Andrea Sboner, Tara A. Gianoulis, Joel Rozowsky, Ashish Agarwal, Michael Snyder, Mark Gerstein (2011). RSEQtools: A modular framework to analyze RNA-Seq data using compact, anonymized data summaries, Bioinformatics 27(2):281-283.

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