Evidence map›Paper›PMID 29945233›Full record

ArticleBioinformatics (Oxford, England)2018

appreci8: a pipeline for precise variant calling integrating 8 tools.

Sarah Sandmann, Mohsen Karimi, Aniek O de Graaf, Christian Rohde, Stefanie Göllner, Julian Varghese, Jan Ernsting, Gunilla Walldin, Bert A van der Reijden, Carsten Müller-Tidow and 4 more

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–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

20 citing papers in PubMed.

  1. Article
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  5. Article
  6. Article
  7. Resources and tools for rare disease variant interpretation.Frontiers in molecular biosciences · 2023
    Review
  8. Article
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  14. 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

14 authors.

Sarah SandmannInstitute of Medical Informatics, University of Münster, Münster, Germany.
Mohsen KarimiDepartment of Medicine Solna, Karolinska Institutet, Stockholm, Sweden.
Aniek O de GraafLaboratory Hematology, RadboudUMC, Nijmegen GA, The Netherlands.
Christian RohdeDepartment of Hematology, Oncology, and Rheumatology, Heidelberg University Hospital, Heidelberg, Germany.
Stefanie GöllnerDepartment of Hematology, Oncology, and Rheumatology, Heidelberg University Hospital, Heidelberg, Germany.
Julian VargheseInstitute of Medical Informatics, University of Münster, Münster, Germany.
Jan ErnstingInstitute of Medical Informatics, University of Münster, Münster, Germany.
Gunilla WalldinDepartment of Medicine Huddinge, Karolinska Institutet, Stockholm, Sweden.
Bert A van der ReijdenLaboratory Hematology, RadboudUMC, Nijmegen GA, The Netherlands.
Carsten Müller-TidowDepartment of Hematology, Oncology, and Rheumatology, Heidelberg University Hospital, Heidelberg, Germany.
Luca MalcovatiDepartments of Hematology Oncology & Molecular Medicine, Fondazione IRCCS Policlinico San Matteo & University of Pavia, Pavia, Italy.
Eva Hellström-LindbergDepartment of Medicine Huddinge, Karolinska Institutet, Stockholm, Sweden.
Joop H JansenLaboratory Hematology, RadboudUMC, Nijmegen GA, The Netherlands.
Martin DugasInstitute of Medical Informatics, University of Münster, Münster, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Motivation: The application of next-generation sequencing in research and particularly in clinical routine requires valid variant calling results. However, evaluation of several commonly used tools has pointed out that not a single tool meets this requirement. False positive as well as false negative calls necessitate additional experiments and extensive manual work. Intelligent combination and output filtration of different tools could significantly improve the current situation. Results: We developed appreci8, an automatic variant calling pipeline for calling single nucleotide variants and short indels by combining and filtering the output of eight open-source variant calling tools, based on a novel artifact- and polymorphism score. Appreci8 was trained on two data sets from patients with myelodysplastic syndrome, covering 165 Illumina samples. Subsequently, appreci8's performance was tested on five independent data sets, covering 513 samples. Variation in sequencing platform, target region and disease entity was considered. All calls were validated by re-sequencing on the same platform, a different platform or expert-based review. Sensitivity of appreci8 ranged between 0.93 and 1.00, while positive predictive value ranged between 0.65 and 1.00. In all cases, appreci8 showed superior performance compared to any evaluated alternative approach. Availability and implementation: Appreci8 is freely available at https://hub.docker.com/r/wwuimi/appreci8/. Sequencing data (BAM files) of the 678 patients analyzed with appreci8 have been deposited into the NCBI Sequence Read Archive (BioProjectID: 388411; https://www.ncbi.nlm.nih.gov/bioproject/PRJNA388411). Supplementary information: Supplementary data are available at Bioinformatics online.

Indexed as

High-Throughput Nucleotide SequencingPolymorphism, Single NucleotideSoftwareComputational BiologyHumansMyelodysplastic Syndromes

Identifiers

PMID29945233
PMCPMC6289140

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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.