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Published on: April 11, 2016
Implementation of Cloud based next generation sequencing data analysis in a clinical laboratory.
Getiria Onsongo, Jesse Erdmann, Michael D Spears
1Research Informatics Support Systems, Minnesota Supercomputing Institute, University of Minnesota, Room 599 Walter Library 117 Pleasant St SE, Minneapolis, MN 55455, USA. kats@umn.edu.
A new Galaxy-based bioinformatics pipeline makes next-generation sequencing (NGS) testing more affordable for clinical diagnostics. This cloud-based solution efficiently analyzes NGS data and identifies genetic variants, overcoming cost barriers in molecular diagnostics.
Area of Science:
- Bioinformatics
- Molecular Diagnostics
- Genomics
Background:
- Next-generation sequencing (NGS) has transformed molecular diagnostics but faces adoption challenges.
- High-throughput sequencing generates large data volumes requiring robust, cost-effective bioinformatics pipelines.
- The substantial computing power needed for NGS data analysis is often prohibitively expensive for clinical labs.
Purpose of the Study:
- To develop and validate a cost-effective bioinformatics pipeline for NGS data analysis in clinical diagnostics.
- To address the computational and financial challenges limiting widespread NGS adoption.
Main Methods:
- Developed a Galaxy-based, cloud-computing data analysis pipeline for NGS.
- Utilized a web-based infrastructure to process sequencing data and identify genetic variants.
- Implemented flexibility in storage cost control, avoiding the need for EBS disk usage.
Main Results:
- The pipeline successfully processed NGS data and identified genetic variants.
- The cloud-based approach proved cost-effective on a per-sample basis.
- No EBS disk usage was required, further reducing operational costs.
Conclusions:
- The bioinformatics pipeline is validated and feasible for implementation in molecular diagnostics.
- Analysis of four samples in duplicate pairs showed 100% concordance in mutation identification.
- The pipeline is currently in clinical use, with identified pathogenic variants confirmed by Sanger sequencing.
