Evidence map›Paper›PMID 28233799›Full record

ArticleScientific reports2017

Evaluating Variant Calling Tools for Non-Matched Next-Generation Sequencing Data.

Sarah Sandmann, Aniek O de Graaf, Mohsen Karimi, Bert A van der Reijden, Eva Hellström-Lindberg, Joop H Jansen, Martin Dugas

Abstract readComparative StudyEvaluation Study
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 113 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
113citing papers in PubMed, 1 pooled it
–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

113 citing papers in PubMed, 1 synthesis or guideline pooled it.

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53 more citing papers are in PubMed but not listed here.

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.

Sarah SandmannInstitute of Medical Informatics, University of Münster, Münster, 48149, Germany.
Aniek O de GraafLaboratory Hematology, RadboudUMC, Nijmegen, 6525, Netherlands.
Mohsen KarimiCenter for Hematology and Regenerative Medicine, Department of Medicine Huddinge, Karolinska Institutet, Stockholm, 14186, Sweden.
Bert A van der ReijdenLaboratory Hematology, RadboudUMC, Nijmegen, 6525, Netherlands.
Eva Hellström-LindbergCenter for Hematology and Regenerative Medicine, Department of Medicine Huddinge, Karolinska Institutet, Stockholm, 14186, Sweden.
Joop H JansenLaboratory Hematology, RadboudUMC, Nijmegen, 6525, Netherlands.
Martin DugasInstitute of Medical Informatics, University of Münster, Münster, 48149, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Valid variant calling results are crucial for the use of next-generation sequencing in clinical routine. However, there are numerous variant calling tools that usually differ in algorithms, filtering strategies, recommendations and thus, also in the output. We evaluated eight open-source tools regarding their ability to call single nucleotide variants and short indels with allelic frequencies as low as 1% in non-matched next-generation sequencing data: GATK HaplotypeCaller, Platypus, VarScan, LoFreq, FreeBayes, SNVer, SAMtools and VarDict. We analysed two real datasets from patients with myelodysplastic syndrome, covering 54 Illumina HiSeq samples and 111 Illumina NextSeq samples. Mutations were validated by re-sequencing on the same platform, on a different platform and expert based review. In addition we considered two simulated datasets with varying coverage and error profiles, covering 50 samples each. In all cases an identical target region consisting of 19 genes (42,322 bp) was analysed. Altogether, no tool succeeded in calling all mutations. High sensitivity was always accompanied by low precision. Influence of varying coverages- and background noise on variant calling was generally low. Taking everything into account, VarDict performed best. However, our results indicate that there is a need to improve reproducibility of the results in the context of multithreading.

Indexed as

Polymorphism, Single NucleotideComputational BiologyHigh-Throughput Nucleotide SequencingHumansSensitivity and SpecificitySequence Analysis, DNA

Identifiers

PMID28233799
PMCPMC5324109

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Registered trials

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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.