Evidence map›Paper›PMID 35467413›Full record

ArticlemBio2022

Meaningful Use of Pathogen Genomic Data.

Taj Azarian

Abstract readComment
In one paragraph

Article in mBio, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

1 author.

Taj AzarianBurnett School of Biomedical Sciences, University of Central Floridagrid.170430.1, Orlando, Florida, USA.ORCID 0000-0002-8611-5241

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Population genomic analysis is a powerful tool to understand the evolutionary history of pathogens and the factors contributing to the success or failure of lineages. These studies have significant implications for human health, as evident from our ongoing tracking of SARS-CoV-2. In their article, Gill et al. (J. L. Gill, J. Hedge, D. J. Wilson, and R. C. MacLean, mBio 12:e02168-21, 2021, https://doi.org/10.1128/mBio.02168-21) demonstrate the utility of pathogen genomic data by comprehensively elucidating the origin of methicillin-resistant Staphylococcus aureus ST239. To accomplish this, they leveraged newly developed tools for querying large genomic data sets. Overall, these analyses rely on the availability of representative genomic data along with their associated metadata-information about where and when samples were collected, clinical and epidemiological characteristics, and phenotypic properties. However, in many instances, these data are missing. Here, I borrow the term "meaningful use" from the Health IT field to describe the need to maximize the utility of genomic data and make suggestions for how to address the current limitations.

Indexed as

COVID-19Methicillin-Resistant Staphylococcus aureusStaphylococcal InfectionsBiological EvolutionGenomicsHumansSARS-CoV-2bioinformaticsgenomic databasesgenomic epidemiologyMRSApopulation genomicsStaphylococcus aureus

Identifiers

PMID35467413
PMCPMC9239187

What OpenQuestion holds

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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.