- Title
- TAPES: A tool for assessment and prioritisation in exome studies
- Creator
- Xavier, Alexandre; Scott, Rodney J.; Talseth-Palmer, Bente A.
- Relation
- PLoS Computational Biology Vol. 15, Issue 10, no. e1007453
- Publisher Link
- http://dx.doi.org/10.1371/journal.pcbi.1007453
- Publisher
- Public Library of Science (PLoS)
- Resource Type
- journal article
- Date
- 2019
- Description
- Next-generation sequencing continues to grow in importance for researchers. Exome sequencing became a widespread tool to further study the genomic basis of Mendelian diseases. In an effort to identify pathogenic variants, reject benign variants and better predict variant effects in downstream analysis, the American College of Medical Genetics (ACMG) published a set of criteria in 2015. While there are multiple publicly available software's available to assign the ACMG criteria, most of them do not take into account multi-sample variant calling formats. Here we present a tool for assessment and prioritisation in exome studies (TAPES, https://github.com/a-xavier/tapes), an open-source tool designed for small-scale exome studies. TAPES can quickly assign ACMG criteria using ANNOVAR or VEP annotated files and implements a model to transform the categorical ACMG criteria into a continuous probability, allowing for a more accurate classification of pathogenicity or benignity of variants. In addition, TAPES can work with cohorts sharing a common phenotype by utilising a simple enrichment analysis, requiring no controls as an input as well as providing powerful filtering and reporting options. Finally, benchmarks showed that TAPES outperforms available tools to detect both pathogenic and benign variants, while also integrating the identification of enriched variants in study cohorts compared to the general population, making it an ideal tool to evaluate a smaller cohort before using bigger scale studies.
- Subject
- pathogenesis; computer software; open source software; cancers and neoplasms; genetics of disease; next-generation sequencing; cohort studies; genomic medicine
- Identifier
- http://hdl.handle.net/1959.13/1417904
- Identifier
- uon:37272
- Identifier
- ISSN:1553-734X
- Rights
- © 2019 Xavier et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
- Language
- eng
- Full Text
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| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
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