Implementation of Cloud based next generation sequencing data analysis in a clinical laboratory

The introduction of next generation sequencing (NGS) has revolutionized molecular diagnostics, though several challenges remain limiting the widespread adoption of NGS testing into clinical practice. One such difficulty includes the development of a robust bioinformatics pipeline that can handle the...

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Veröffentlicht in:BMC research notes 2014-05, Vol.7 (1), p.314-314, Article 314
Hauptverfasser: Onsongo, Getiria, Erdmann, Jesse, Spears, Michael D, Chilton, John, Beckman, Kenneth B, Hauge, Adam, Yohe, Sophia, Schomaker, Matthew, Bower, Matthew, Silverstein, Kevin A T, Thyagarajan, Bharat
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container_issue 1
container_start_page 314
container_title BMC research notes
container_volume 7
creator Onsongo, Getiria
Erdmann, Jesse
Spears, Michael D
Chilton, John
Beckman, Kenneth B
Hauge, Adam
Yohe, Sophia
Schomaker, Matthew
Bower, Matthew
Silverstein, Kevin A T
Thyagarajan, Bharat
description The introduction of next generation sequencing (NGS) has revolutionized molecular diagnostics, though several challenges remain limiting the widespread adoption of NGS testing into clinical practice. One such difficulty includes the development of a robust bioinformatics pipeline that can handle the volume of data generated by high-throughput sequencing in a cost-effective manner. Analysis of sequencing data typically requires a substantial level of computing power that is often cost-prohibitive to most clinical diagnostics laboratories. To address this challenge, our institution has developed a Galaxy-based data analysis pipeline which relies on a web-based, cloud-computing infrastructure to process NGS data and identify genetic variants. It provides additional flexibility, needed to control storage costs, resulting in a pipeline that is cost-effective on a per-sample basis. It does not require the usage of EBS disk to run a sample. We demonstrate the validation and feasibility of implementing this bioinformatics pipeline in a molecular diagnostics laboratory. Four samples were analyzed in duplicate pairs and showed 100% concordance in mutations identified. This pipeline is currently being used in the clinic and all identified pathogenic variants confirmed using Sanger sequencing further validating the software.
doi_str_mv 10.1186/1756-0500-7-314
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subjects Clinical Laboratory Techniques - economics
Cloud computing
Diagnostic equipment (Medical)
DNA sequencing
High-Throughput Nucleotide Sequencing - economics
High-Throughput Nucleotide Sequencing - methods
Humans
Information storage and retrieval
Internet - economics
Nucleotide sequencing
Reproducibility of Results
Sequence Analysis, DNA - economics
Sequence Analysis, DNA - methods
Statistics as Topic
Technical Note
Technology application
title Implementation of Cloud based next generation sequencing data analysis in a clinical laboratory
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