Evidence map›Paper›PMID 35342619›Full record

ArticleF1000Research2021

Methods for sequencing the pandemic: benefits of rapid or high-throughput processing.

Megan L Folkerts, Darrin Lemmer, Ashlyn Pfeiffer, Danielle Vasquez, Chris French, Amber Jones, Marjorie Nguyen, Brendan Larsen, W Tanner Porter, Krystal Sheridan and 2 more

Open access · goldAbstract read
In one paragraph

Article in F1000Research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
0.6field-weighted citation impact, top 31% of its field
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

10 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. DETECTION OF SARS-COV-2 IN A SQUIRREL MONKEY (Journal of zoo and wildlife medicine : official publication of the American Association of Zoo Veterinarians · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 2 institutions in 1 country.

Megan L FolkertsPathogen Genomics Division, Translational Genomics Research Institute, Flagstaff, AZ, 86005, USA.ORCID 0000-0001-7430-1701
Darrin LemmerPathogen Genomics Division, Translational Genomics Research Institute, Flagstaff, AZ, 86005, USA.ORCID 0000-0003-2785-6928
Ashlyn PfeifferPathogen Genomics Division, Translational Genomics Research Institute, Flagstaff, AZ, 86005, USA.
Danielle VasquezPathogen Genomics Division, Translational Genomics Research Institute, Flagstaff, AZ, 86005, USA.
Chris FrenchPathogen Genomics Division, Translational Genomics Research Institute, Flagstaff, AZ, 86005, USA.
Amber JonesPathogen Genomics Division, Translational Genomics Research Institute, Flagstaff, AZ, 86005, USA.
Marjorie NguyenPathogen Genomics Division, Translational Genomics Research Institute, Flagstaff, AZ, 86005, USA.
Brendan LarsenDepartment of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, 85721, USA.
W Tanner PorterPathogen Genomics Division, Translational Genomics Research Institute, Flagstaff, AZ, 86005, USA.
Krystal SheridanPathogen Genomics Division, Translational Genomics Research Institute, Flagstaff, AZ, 86005, USA.
Jolene R BowersPathogen Genomics Division, Translational Genomics Research Institute, Flagstaff, AZ, 86005, USA.
David M EngelthalerPathogen Genomics Division, Translational Genomics Research Institute, Flagstaff, AZ, 86005, USA.
Translational Genomics Research Institute · USUniversity of Arizona · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genomic epidemiology has proven successful for real-time and retrospective monitoring of small and large-scale outbreaks. Here, we report two genomic sequencing and analysis strategies for rapid-turnaround or high-throughput processing of metagenomic samples. The rapid-turnaround method was designed to provide a quick phylogenetic snapshot of samples at the heart of active outbreaks, and has a total turnaround time of <48 hours from raw sample to analyzed data. The high-throughput method, first reported here for SARS-CoV2, was designed for semi-retrospective data analysis, and is both cost effective and highly scalable. Though these methods were developed and utilized for the SARS-CoV-2 pandemic response in Arizona, U.S, we envision their use for infectious disease epidemiology in the 21

Indexed as

COVID-19PandemicsHumansPhylogenyRetrospective StudiesRNA, ViralSARS-CoV-2RNA, ViralGenomic epidemiologyphylogeneticsSARS-CoV2sequencing methodstargeted genomics

Identifiers

PMID35342619
PMCPMC8921685
OpenAlexW3124565698

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.