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Practical estimation of cloud storage costs for clinical genomic data
1Department of Laboratory Medicine, University of Washington, Seattle, WA, USA.
Practical Laboratory Medicine
|June 13, 2020
Summary
Cloud storage offers economical solutions for clinical next-generation sequencing (NGS) data. Optimizing file size and utilizing archival storage significantly reduces costs per test, making cloud solutions practical for laboratories.
Area of Science:
- Genomics
- Bioinformatics
- Cloud Computing
Background:
- Clinical laboratories are increasingly adopting cloud storage for oncology and germline testing data.
- While cloud storage offers benefits like scalability and lower per-GB prices, accurate cost analysis for next-generation sequencing (NGS) data is complex due to usage-based pricing.
Purpose of the Study:
- To develop a user-friendly tool for estimating costs and usage of cloud storage for clinical NGS laboratories.
- To provide detailed forecasts for storage costs over 1-20 year timeframes, considering various parameters.
Main Methods:
- Developed a web-based tool (https://ngscosts.info) for cost and usage estimation.
- Integrated parameters such as test volumes, growth rates, data compression, retention policies, and re-access rates.
- Enabled comparison of storage options across major cloud providers with visualized outputs.
Main Results:
- Reducing file size through compression and rapid transfer to archival storage significantly decreases the average cost per test.
- Re-accessing data from archival storage tiers had a minimal impact on the overall cost per test.
Conclusions:
- Cloud storage is becoming an economical and workflow-friendly option for clinical NGS data due to declining prices and improved storage/retrieval options.
- The developed tool aids laboratories in exploring and forecasting cloud storage solutions tailored for their specific needs.
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