Evidence map›Paper›PMID 31830259›Full record

ArticleBioinformatics (Oxford, England)2020

ClinVAP: a reporting strategy from variants to therapeutic options.

Bilge Sürün, Charlotta P I Schärfe, Mathew R Divine, Julian Heinrich, Nora C Toussaint, Lukas Zimmermann, Janina Beha, Oliver Kohlbacher

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Article
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.

Bilge SürünDepartment of Computer Science, Applied Bioinformatics, Tübingen 72076, Germany.
Charlotta P I SchärfeDepartment of Computer Science, Applied Bioinformatics, Tübingen 72076, Germany.
Mathew R DivineDepartment of Computer Science, Applied Bioinformatics, Tübingen 72076, Germany.
Julian HeinrichDepartment of Computer Science, Applied Bioinformatics, Tübingen 72076, Germany.
Nora C ToussaintNEXUS Personalized Health Technologies, ETH Zurich, Zurich 8093, Switzerland.
Lukas ZimmermannTranslational Bioinformatics, University Hospital Tübingen, Tübingen 72076, Germany.
Janina BehaCenter for Personalized Medicine, University Hospital Tübingen, Tübingen 72076, Germany.
Oliver KohlbacherDepartment of Computer Science, Applied Bioinformatics, Tübingen 72076, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

motivationNext-generation sequencing has become routine in oncology and opens up new avenues of therapies, particularly in personalized oncology setting. An increasing number of cases also implies a need for a more robust, automated and reproducible processing of long lists of variants for cancer diagnosis and therapy. While solutions for the large-scale analysis of somatic variants have been implemented, existing solutions often have issues with reproducibility, scalability and interoperability.

resultsClinical Variant Annotation Pipeline (ClinVAP) is an automated pipeline which annotates, filters and prioritizes somatic single nucleotide variants provided in variant call format. It augments the variant information with documented or predicted clinical effect. These annotated variants are prioritized based on driver gene status and druggability. ClinVAP is available as a fully containerized, self-contained pipeline maximizing reproducibility and scalability allowing the analysis of larger scale data. The resulting JSON-based report is suited for automated downstream processing, but ClinVAP can also automatically render the information into a user-defined template to yield a human-readable report. AVAILABILITY AND IMPLEMENTATION: ClinVAP is available at https://github.com/PersonalizedOncology/ClinVAP. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

High-Throughput Nucleotide SequencingSoftwareHumansMedical OncologyReproducibility of Results

Identifiers

PMID31830259
PMCPMC7141851

What OpenQuestion holds

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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.