ArticlePractical laboratory medicine2020
Practical estimation of cloud storage costs for clinical genomic data.
Article in Practical laboratory medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Biomedical blockchain with practical implementations and quantitative evaluations: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2024Pooled it
- Making genomic data FAIR through effective Data Portals.Scientific data · 2025Article
- Review
- Storing paediatric genomic data for sequential interrogation across the lifespan.Journal of medical ethics · 2025Article
- Actual usage assessment among cloud storage consumers in the Philippines using a machine learning ensemble approach.Scientific reports · 2024Article
- It Is in Our DNA: Bringing Electronic Health Records and Genomic Data Together for Precision Medicine.JMIR bioinformatics and biotechnology · 2024Article
- One Step Ahead in Realizing Pharmacogenetics in Low- and Middle-Income Countries: What Should We Do?Journal of multidisciplinary healthcare · 2024Review
- Reproducible, scalable, and shareable analysis pipelines with bioinformatics workflow managers.Nature methods · 2021Review
- Practical Aspects of Implementing and Applying Health Care Cloud Computing Services and Informatics to Cancer Clinical Trial Data.JCO clinical cancer informatics · 2021Article
- Next-Generation Sequencing Applications for Inherited Retinal Diseases.International journal of molecular sciences · 2021Review
- Time in Range as a Research Outcome Measure.Diabetes spectrum : a publication of the American Diabetes Association · 2021Article
- Practical guide for managing large-scale human genome data in research.Journal of human genetics · 2021Review
- Exploring the potential value of satellite remote sensing to monitor chlorophyll-a for US lakes and reservoirs.Environmental monitoring and assessment · 2020Article
- Managing the Transition to Widespread Metagenomic Monitoring: Policy Considerations for Future Biosurveillance.Health securityArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLaboratories 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.
methodsWe 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.
resultsTwo 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 archival storage tiers was not found to dramatically increase the cost of storage per test.
conclusionsSteady declines in cloud storage pricing, as well as new options for storage and retrieval, make storing clinical NGS data on the cloud economical and friendly to laboratory workflows. Our web-based tool makes it possible to explore and compare cloud storage solutions and provide forecasts specifically for clinical NGS laboratories.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.