Evidence map›Paper›PMID 30703562›Full record

ReviewThe Journal of molecular diagnostics : JMD2019

Considerations for Genomic Data Privacy and Security when Working in the Cloud.

Alexis B Carter

Abstract readReview
PubMed Publisher
In one paragraph

Review in The Journal of molecular diagnostics : JMD, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed.

  1. Article
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  13. A secure system for genomics clinical decision support.Journal of biomedical informatics · 2020
    Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

1 author.

Alexis B CarterChildren's Healthcare of Atlanta, Laboratory Administration, Atlanta, Georgia; Informatics Subdivision Leadership, Association for Molecular Pathology, Bethesda, Maryland. Electronic address: alexis.carter@choa.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Next-generation sequencing produces large amounts of data. The complexity and data management issues associated with next-generation sequencing have led many laboratories to turn to cloud services, especially when internal information technology infrastructure is inadequate to support data requirements. In addition, public cloud repositories of variants are being increasingly utilized, and their data sets are being populated through crowdsourcing submissions of human genetic variation identified within laboratories. The purpose of this review is to describe the challenges of managing genomic data in the cloud and to discuss potential strategies to surmount these challenges in a compliant manner. The definitions and advantages of cloud systems are outlined. Special regulatory considerations for laboratories are included, and strategies for compliance in the US regulatory environment for genetic information in clinical patient care as well as in research and public databases are also discussed.

Indexed as

Genetic PrivacyGenome, HumanGenomicsCloud ComputingDatabases, GeneticGovernment RegulationHealth Information ManagementHealth PolicyHumansResearch

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.