A pipeline‐friendly software tool for genome diagnostics to prioritize genes by matching patient symptoms to literature. Issue 1 (10th August 2020)
- Record Type:
- Journal Article
- Title:
- A pipeline‐friendly software tool for genome diagnostics to prioritize genes by matching patient symptoms to literature. Issue 1 (10th August 2020)
- Main Title:
- A pipeline‐friendly software tool for genome diagnostics to prioritize genes by matching patient symptoms to literature
- Authors:
- van der Velde, K. Joeri
van den Hoek, Sander
van Dijk, Freerk
Hendriksen, Dennis
van Diemen, Cleo C.
Johansson, Lennart F.
Abbott, Kristin M.
Deelen, Patrick
Sikkema‐Raddatz, Birgit
Swertz, Morris A. - Abstract:
- Abstract: Despite an explosive growth of next‐generation sequencing data, genome diagnostics only provides a molecular diagnosis to a minority of patients. Software tools that prioritize genes based on patient symptoms using known gene‐disease associations may complement variant filtering and interpretation to increase chances of success. However, many of these tools cannot be used in practice because they are embedded within variant prioritization algorithms, or exist as remote services that cannot be relied upon or are unacceptable because of legal/ethical barriers. In addition, many tools are not designed for command‐line usage, closed‐source, abandoned, or unavailable. We present Variant Interpretation using Biomedical literature Evidence (VIBE), a tool to prioritize disease genes based on Human Phenotype Ontology codes. VIBE is a locally installed executable that ensures operational availability and is built upon DisGeNET‐RDF, a comprehensive knowledge platform containing gene‐disease associations mostly from literature and variant‐disease associations mostly from curated source databases. VIBE's command‐line interface and output are designed for easy incorporation into bioinformatic pipelines that annotate and prioritize variants for further clinical interpretation. We evaluate VIBE in a benchmark based on 305 patient cases alongside seven other tools. Our results demonstrate that VIBE offers consistent performance with few cases missed, but we also find highAbstract: Despite an explosive growth of next‐generation sequencing data, genome diagnostics only provides a molecular diagnosis to a minority of patients. Software tools that prioritize genes based on patient symptoms using known gene‐disease associations may complement variant filtering and interpretation to increase chances of success. However, many of these tools cannot be used in practice because they are embedded within variant prioritization algorithms, or exist as remote services that cannot be relied upon or are unacceptable because of legal/ethical barriers. In addition, many tools are not designed for command‐line usage, closed‐source, abandoned, or unavailable. We present Variant Interpretation using Biomedical literature Evidence (VIBE), a tool to prioritize disease genes based on Human Phenotype Ontology codes. VIBE is a locally installed executable that ensures operational availability and is built upon DisGeNET‐RDF, a comprehensive knowledge platform containing gene‐disease associations mostly from literature and variant‐disease associations mostly from curated source databases. VIBE's command‐line interface and output are designed for easy incorporation into bioinformatic pipelines that annotate and prioritize variants for further clinical interpretation. We evaluate VIBE in a benchmark based on 305 patient cases alongside seven other tools. Our results demonstrate that VIBE offers consistent performance with few cases missed, but we also find high complementarity among all tested tools. VIBE is a powerful, free, open source and locally installable solution for prioritizing genes based on patient symptoms. Project source code, documentation, benchmark and executables are available at https://github.com/molgenis/vibe . Abstract : Gene prioritization tool output and causal gene rank for all patient cases. Each dot represents a patient case (ie, set of Human Phenotype Ontology codes) for which the causal gene was prioritized by one of eight benchmarked tools. Shown are the absolute ranks of the causal genes vs the total number of candidate genes returned by a tool. The colored labels indicate which dot belongs to which tool, as well as show the number of missed genes for each tool, where the causal gene was not present in the output gene list. … (more)
- Is Part Of:
- Advanced genetics. Volume 1:Issue 1(2021)
- Journal:
- Advanced genetics
- Issue:
- Volume 1:Issue 1(2021)
- Issue Display:
- Volume 1, Issue 1 (2021)
- Year:
- 2021
- Volume:
- 1
- Issue:
- 1
- Issue Sort Value:
- 2021-0001-0001-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2020-08-10
- Subjects:
- benchmark -- command‐line -- gene prioritization -- genome diagnostics -- next‐generation sequencing -- patient symptoms -- primary literature
Genetics -- Periodicals
Genomics -- Periodicals
Genomics
Genetics
Genetics
Genomics
Electronic journals
Periodicals
576.5 - Journal URLs:
- https://onlinelibrary.wiley.com/toc/26416573/2020/1/1 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/ggn2.10023 ↗
- Languages:
- English
- ISSNs:
- 2641-6573
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
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- 15206.xml