Identifying actionable variants in cancer - The dual web and batch processing tool MTB-report
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- dc.contributor.author Kurz, Nadine S.
- dc.contributor.author Perera Bel, Júlia
- dc.contributor.author Höltermann, Charlotte
- dc.contributor.author Tucholski, Tim
- dc.contributor.author Yang, Jingyu
- dc.contributor.author Beissbarth, Tim
- dc.contributor.author Dönitz, Jürgen
- dc.date.accessioned 2023-02-15T07:33:11Z
- dc.date.available 2023-02-15T07:33:11Z
- dc.date.issued 2022
- dc.description.abstract Next-generation sequencing methods continuously provide clinicians and researchers in precision oncology with growing numbers of genomic variants found in cancer. However, manually interpreting the list of variants to identify reliable targets is an inefficient and cumbersome process that does not scale with the increasing number of cases. Support by computer systems is needed for the analysis of large scale experiments and clinical studies to identify new targets and therapies, and user-friendly applications are needed in molecular tumor boards to support clinicians in their decision-making processes. The MTB-Report tool annotates, filters and sorts genetic variants with information from public databases, providing evidence on actionable variants in both scenarios. A web interface supports medical doctors in the tumor board, and a command line mode allows batch processing of large datasets. The MTB-Report tool is available as an R implementation as well as a Docker image to provide a tool that runs out-of-the-box. Moreover, containerization ensures a stable application that delivers reproducible results over time. A public version of the web interface is available at: http://mtb.bioinf.med.uni-goettingen.de/mtb-report.
- dc.format.mimetype application/pdf
- dc.identifier.citation Kurz NS, Perera-Bel J, Höltermann C, Tucholski T, Yang J, Beissbarth T, Dönitz J. Identifying actionable variants in cancer - The dual web and batch processing tool MTB-report. Stud Health Technol Inform. 2022 Aug 17;296:73-80. DOI: 10.3233/SHTI220806
- dc.identifier.doi http://dx.doi.org/10.3233/SHTI220806
- dc.identifier.issn 0926-9630
- dc.identifier.uri http://hdl.handle.net/10230/55784
- dc.language.iso eng
- dc.publisher IOS Press
- dc.relation.ispartof Stud Health Technol Inform. 2022 Aug 17;296:73-80
- dc.rights © 2022 The authors and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).
- dc.rights.accessRights info:eu-repo/semantics/openAccess
- dc.rights.uri https://creativecommons.org/licenses/by-nc/4.0/
- dc.subject.keyword Variant interpretation
- dc.subject.keyword Actionable variants
- dc.subject.keyword Molecular profiles
- dc.subject.keyword Molecular tumor board
- dc.subject.keyword Next-generation sequencing
- dc.subject.keyword Precision oncology
- dc.title Identifying actionable variants in cancer - The dual web and batch processing tool MTB-report
- dc.type info:eu-repo/semantics/article
- dc.type.version info:eu-repo/semantics/publishedVersion