Practical estimation of cloud storage costs for clinical genomic data

Practical Laboratory Medicine
Niklas Krumm, Noah Hoffman

Abstract

Laboratories performing clinical high-throughput sequencing for oncology and germline testing are increasingly migrating their data storage to cloud-based solutions. Cloud-based storage has several advantages, such as low per-GB prices, scalability, and minimal fixed costs; however, while these solutions tout ostensibly simple usage-based pricing plans, practical cost analysis of cloud storage for NGS data storage is not straightforward. We developed an easy-to-use tool designed specifically for cost and usage estimation for laboratories performing clinical NGS testing (https://ngscosts.info). Our tool enables quick exploration of dozens of storage options across three major cloud providers, and provides complex cost and usage forecasts over 1-20 year timeframes. Parameters include current test volumes, growth rate, data compression, data retention policies, and case re-access rates. Outputs include an easy-to-visualize chart of total data stored, yearly and lifetime costs, and a "cost per test" estimate. Two factors were found to markedly decrease the average cost per test: 1) reducing total file size, including through the use of compression, 2) rapid transfer to "cold" or archival storage. In contrast, re-access of data from...Continue Reading

Citations

Sep 16, 2020·Nature Genetics·Amalio Telenti, Xiaoqian Jiang
Oct 25, 2020·Journal of Human Genetics·Tomoya TanjoMasao Nagasaki
Dec 3, 2020·Environmental Monitoring and Assessment·Michael PapenfusKeith Loftin
Nov 21, 2020·Genome Génome / Conseil National De Recherches Canada·Ritesh Krishna, Vadim Elisseev
Jun 3, 2021·International Journal of Molecular Sciences·Adrian DockeryG Jane Farrar
Jun 22, 2021·Diabetes Spectrum : a Publication of the American Diabetes Association·Joseph G TimmonsJohn R Petrie

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Software Mentioned

Google Cloud
AWS
Azure
fastq
Google Compute Platform ( GCP
Azure Cloud
Alphabet
ngscosts
GCP Archive

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