ArticleSource code for biology and medicine2016
A new tool for prioritization of sequence variants from whole exome sequencing data.
Article in Source code for biology and medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Transformative Applications and Innovations in Next-Generation Sequencing Data Analysis.Journal of applied genetics · 2026Review
- Variant Impact Predictor database (VIPdb), version 2: trends from three decades of genetic variant impact predictors.Human genomics · 2024Article
- Variant Impact Predictor database (VIPdb), version 2: Trends from 25 years of genetic variant impact predictors.bioRxiv : the preprint server for biology · 2024Article
- Phenotypic and immune functional profiling of patients with suspected Mendelian Susceptibility to Mycobacterial Disease in South Africa.BMC immunology · 2021Article
- Identification of a novel WAS mutation in a South African patient presenting with atypical Wiskott-Aldrich syndrome: a case report.BMC medical genetics · 2020Article
- Identifying individual risk rare variants using protein structure guided local tests (POINT).PLoS computational biology · 2019Article
- Exome sequencing identifies a novel TTC37 mutation in the first reported case of Trichohepatoenteric syndrome (THE-S) in South Africa.BMC medical genetics · 2017Article
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Authors and funding
6 authors.
Funding
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Abstract
backgroundWhole exome sequencing (WES) has provided a means for researchers to gain access to a highly enriched subset of the human genome in which to search for variants that are likely to be pathogenic and possibly provide important insights into disease mechanisms. In developing countries, bioinformatics capacity and expertise is severely limited and wet bench scientists are required to take on the challenging task of understanding and implementing the barrage of bioinformatics tools that are available to them.
resultsWe designed a novel method for the filtration of WES data called TAPER™ (Tool for Automated selection and Prioritization for Efficient Retrieval of sequence variants).
conclusionsTAPER™ implements a set of logical steps by which to prioritize candidate variants that could be associated with disease and this is aimed for implementation in biomedical laboratories with limited bioinformatics capacity. TAPER™ is free, can be setup on a Windows operating system (from Windows 7 and above) and does not require any programming knowledge. In summary, we have developed a freely available tool that simplifies variant prioritization from WES data in order to facilitate discovery of disease-causing genes.
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