Robust and Portable Workflow-based tolls for MRNA and Genome re-sequencing

University Of Southern California, Los Angeles CA

Investigators

Linked publications, trials & patents

Abstract

DESCRIPTION (provided by applicant): Sequencing of DNA and cDNA libraries on next-generation sequencing (NGS) platforms has become the method of choice for genomic and transcriptional analyses. One obstacle that inhibits wider adoption of NGS techniques is the lack of comprehensive, yet easy to use software packages with which to conduct data analysis. To meet this need, we have developed RseqFlow, a set of common analytic modules for the analysis of RNA-seq data which is formalized into an easy to use workflow. The workflow is managed by the Pegasus Workflow Management System (WMS), which maps the modules to available computational resources and automatically executes the steps in the appropriate order. A Virtual Machine (VM) was created for the software package which eliminates complex configuration and installation steps. In this proposal, we plan to extend RseqFlow to include more analytic functions and also to generalize it to work for multiple model organisms including the Mouse, Worm, Fruit fly, Plant and Yeast. We also propose the development of a similar workflow for the analysis of genome re-sequencing data. Both of the workflows will take advantage of several analytic tools we have developed, including PerM (short read alignment), ComB (SNP Calling), Clippers (Indel/Junction detection), and WeaV (de novo assembly). One of the unique features of our workflow is an iterative alignment strategy where sequence variants are used to update the sequence and improve alignment accuracy which in turn affords us the ability to accurately determine not only SNPs and indels but also structural and copy-number variations. A final effort will include combining the workflows for RNA-seq data and genome re-sequencing data to perform RNA editing analysis. All programs developed under this proposal will be rigorously tested on a number of different data sets and on multiple computational platfonns, and use sound software engineering practices. All software released under this proposal will be open source and greatly benefit many biological projects which incorporate DNA and RNA sequencing approaches.