Unknown

Dataset Information

0

ClinVAP: a reporting strategy from variants to therapeutic options.


ABSTRACT: MOTIVATION:Next-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. RESULTS:Clinical 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.

SUBMITTER: Surun B 

PROVIDER: S-EPMC7141851 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

altmetric image

Publications

ClinVAP: a reporting strategy from variants to therapeutic options.

Sürün Bilge B   Schärfe Charlotta P I CPI   Divine Mathew R MR   Heinrich Julian J   Toussaint Nora C NC   Zimmermann Lukas L   Beha Janina J   Kohlbacher Oliver O  

Bioinformatics (Oxford, England) 20200401 7


<h4>Motivation</h4>Next-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 interop  ...[more]

Similar Datasets

| S-EPMC7139252 | biostudies-literature
| S-EPMC5856211 | biostudies-literature
| S-EPMC5537664 | biostudies-literature
| S-EPMC9093055 | biostudies-literature
2017-11-21 | GSE104766 | GEO
| S-EPMC5411274 | biostudies-literature
| S-EPMC9140894 | biostudies-literature
| S-EPMC4514707 | biostudies-other
| S-EPMC7097181 | biostudies-literature
| S-EPMC7424051 | biostudies-literature