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Abstract

Next Generation Sequencing (NGS) is becoming a common tool in the practice of biomedical research and the future of how medicine will be practiced. To keep up with the explosion in new NGS experiments and the growing need in data analysis, we identified bottlenecks of our NGS data analysis workflow, evaluated and tested feasibility of solutions. To address main bottlenecks we incorporated two solutions into our

workflow: (1) Globus Genomics, a well-maintained cloud based sequencing data analysis framework which leverage advanced tools and data management, and (2) GenomAnalytics from GenomOncology, an interactive platform for data integration, annotation, filtering an interpretation. We also evaluated current methods, and developed Standard Operation Procedures (SOPs) for the most common data types; RNA-seq, exome-seq, and whole genome resequencing. This workflow provides high quality, standardized, and low-cost NGS data analysis in a reasonably short turnaround time to all investigators. The system is self-sustaining and scalable to process larger number of samples with minimal need for additional personnel.

Publication Date

11-14-2014

Disciplines

Genetics and Genomics

Genomic Sequencing Data Analysis Workflow for Bioinformatics Core Facilities

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