Evidence map›Paper›PMID 37891004›Full record

ArticleRNA (New York, N.Y.)2023

VODKA2: a fast and accurate method to detect non-standard viral genomes from large RNA-seq data sets.

Emna Achouri, Sébastien A Felt, Matthew Hackbart, Nicole S Rivera-Espinal, Carolina B López

Open access · bronzeAbstract read
In one paragraph

Article in RNA (New York, N.Y.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
7.1field-weighted citation impact, top 4% 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

16 citing papers in PubMed, 18 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Emna AchouriDepartment of Molecular Microbiology and Center for Women's Infectious Disease Research, Washington University School of Medicine, St. Louis, Missouri 63110, USA.ORCID 0009-0006-4092-164X
Sébastien A FeltDepartment of Molecular Microbiology and Center for Women's Infectious Disease Research, Washington University School of Medicine, St. Louis, Missouri 63110, USA.ORCID 0000-0003-2942-7203
Matthew HackbartDepartment of Molecular Microbiology and Center for Women's Infectious Disease Research, Washington University School of Medicine, St. Louis, Missouri 63110, USA.ORCID 0000-0001-6244-6292
Nicole S Rivera-EspinalDepartment of Molecular Microbiology and Center for Women's Infectious Disease Research, Washington University School of Medicine, St. Louis, Missouri 63110, USA.
Carolina B LópezDepartment of Molecular Microbiology and Center for Women's Infectious Disease Research, Washington University School of Medicine, St. Louis, Missouri 63110, USA clopezzalaquett@wustl.edu.ORCID 0000-0002-7669-6572
Washington University in St. Louis · US

Funding

Defective Viral genomes in RSV pathogenesisR01AI137062 · NIAID · WASHINGTON UNIVERSITY · PI Carolina B. Lopez · 2018 to 2026
$4.2M
Mechanisms of DDO AdjuvancyR01AI134862 · NIAID · WASHINGTON UNIVERSITY · PI LOPEZ, CAROLINA B. · 2018 to 2022
$2.4M
NIAID NIH HHS R01 AI134862NIAID NIH HHS R01 AI137062
6 · The paper itself

Abstract

During viral replication, viruses carrying an RNA genome produce non-standard viral genomes (nsVGs), including copy-back viral genomes (cbVGs) and deletion viral genomes (delVGs), that play a crucial role in regulating viral replication and pathogenesis. Because of their critical roles in determining the outcome of RNA virus infections, the study of nsVGs has flourished in recent years, exposing a need for bioinformatic tools that can accurately identify them within next-generation sequencing data obtained from infected samples. Here, we present our data analysis pipeline, Viral Opensource DVG Key Algorithm 2 (VODKA2), that is optimized to run on a parallel computing environment for fast and accurate detection of nsVGs from large data sets.

Indexed as

AlgorithmsGenome, ViralComputational BiologyRNA-SeqRNA, ViralVirus ReplicationRNA, Viralbioinformaticsdefective viral genomesRNA-seqviral genomesVODKA2

Identifiers

PMID37891004
PMCPMC10726161
OpenAlexW4387968960

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.