Evidence map›Paper›PMID 35332213›Full record

ArticleScientific reports2022

The ViReflow pipeline enables user friendly large scale viral consensus genome reconstruction.

Niema Moshiri, Kathleen M Fisch, Amanda Birmingham, Peter DeHoff, Gene W Yeo, Kristen Jepsen, Louise C Laurent, Rob Knight

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
3.2field-weighted citation impact, top 8% 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

11 citing papers in PubMed, 21 citations in OpenAlex.

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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

8 authors at 1 institution in 1 country.

Niema MoshiriDepartment of Computer Science & Engineering, University of California San Diego, La Jolla, CA, USA. niema@ucsd.edu.
Kathleen M FischCenter for Computational Biology and Bioinformatics, University of California San Diego, La Jolla, CA, USA.
Amanda BirminghamCenter for Computational Biology and Bioinformatics, University of California San Diego, La Jolla, CA, USA.
Peter DeHoffDepartment of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Diego, La Jolla, CA, USA.
Gene W YeoDepartment of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA.
Kristen JepsenInstitute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA.
Louise C LaurentDepartment of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Diego, La Jolla, CA, USA.
Rob KnightDepartment of Computer Science & Engineering, University of California San Diego, La Jolla, CA, USA.
University of California San Diego · US

Funding

UC San Diego Clinical and Translational Research InstituteUL1TR001442 · NCATS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI FIRESTEIN, GARY S, HOGARTH, MICHAEL · 2015 to 2024
$88.3M
Illumina NovaSeq 6000 Sequencing SystemS10OD026929 · OD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI JEPSEN, KRISTEN LYNN · 2019 to 2019
$600k
CDC HHS 75D30120C09795National Science Foundation 2028040National Science Foundation 2038509NCATS NIH HHS UL1 TR001442NIH HHS S10 OD026929
6 · The paper itself

Abstract

Throughout the COVID-19 pandemic, massive sequencing and data sharing efforts enabled the real-time surveillance of novel SARS-CoV-2 strains throughout the world, the results of which provided public health officials with actionable information to prevent the spread of the virus. However, with great sequencing comes great computation, and while cloud computing platforms bring high-performance computing directly into the hands of all who seek it, optimal design and configuration of a cloud compute cluster requires significant system administration expertise. We developed ViReflow, a user-friendly viral consensus sequence reconstruction pipeline enabling rapid analysis of viral sequence datasets leveraging Amazon Web Services (AWS) cloud compute resources and the Reflow system. ViReflow was developed specifically in response to the COVID-19 pandemic, but it is general to any viral pathogen. Importantly, when utilized with sufficient compute resources, ViReflow can trim, map, call variants, and call consensus sequences from amplicon sequence data from 1000 SARS-CoV-2 samples at 1000X depth in < 10 min, with no user intervention. ViReflow's simplicity, flexibility, and scalability make it an ideal tool for viral molecular epidemiological efforts.

Indexed as

COVID-19SoftwareGenome, ViralHumansPandemicsSARS-CoV-2

Identifiers

PMID35332213
PMCPMC8943356
OpenAlexW4220962429

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.