Evidence map›Paper›PMID 35176018›Full record

ArticlePLoS computational biology2022

Tool evaluation for the detection of variably sized indels from next generation whole genome and targeted sequencing data.

Ning Wang, Vladislav Lysenkov, Katri Orte, Veli Kairisto, Juhani Aakko, Sofia Khan, Laura L Elo

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2022. 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
2.2field-weighted citation impact, top 12% 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

18 citing papers in PubMed, 26 citations in OpenAlex.

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  12. Hereditary Renal Cancer Syndromes.Medical sciences (Basel, Switzerland) · 2024
    Review
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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

7 authors at 2 institutions in 1 country.

Ning WangTurku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland.ORCID 0000-0002-1275-4710
Vladislav LysenkovTurku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland.ORCID 0000-0002-1468-1631
Katri OrteDepartment of Pathology, Laboratory Division, Turku University Hospital, Turku, Finland.ORCID 0000-0002-0353-6826
Veli KairistoDepartment of Genomics, Laboratory Division, Turku University Hospital, Turku, Finland.ORCID 0000-0002-0562-8054
Juhani AakkoTurku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland.ORCID 0000-0003-4142-3256
Sofia KhanTurku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland.
Laura L EloTurku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland.ORCID 0000-0001-5648-4532
Åbo Akademi University · FITurku University Hospital · FI

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Insertions and deletions (indels) in human genomes are associated with a wide range of phenotypes, including various clinical disorders. High-throughput, next generation sequencing (NGS) technologies enable the detection of short genetic variants, such as single nucleotide variants (SNVs) and indels. However, the variant calling accuracy for indels remains considerably lower than for SNVs. Here we present a comparative study of the performance of variant calling tools for indel calling, evaluated with a wide repertoire of NGS datasets. While there is no single optimal tool to suit all circumstances, our results demonstrate that the choice of variant calling tool greatly impacts the precision and recall of indel calling. Furthermore, to reliably detect indels, it is essential to choose NGS technologies that offer a long read length and high coverage coupled with specific variant calling tools.

Indexed as

Computational BiologyINDEL MutationGenome, HumanHigh-Throughput Nucleotide SequencingHumansPolymorphism, Single Nucleotide

Identifiers

PMID35176018
PMCPMC8916674
OpenAlexW4213328665

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.