TAPES: A tool for assessment and prioritisation in exome studies.

Publisher: Public Library of Science Country of Publication: United States NLM ID: 101238922 Publication Model: eCollection Cited Medium: Internet ISSN: 1553-7358 (Electronic) Linking ISSN: 1553734X NLM ISO Abbreviation: PLoS Comput Biol Subsets: MEDLINE

Original Publication: San Francisco, CA : Public Library of Science, [2005]-

Computational Biology/*methods ; Exome/*genetics ; Sequence Analysis, DNA/*methods; Genetic Variation/genetics ; Genome, Human/genetics ; Genomics/methods ; High-Throughput Nucleotide Sequencing/methods ; Humans ; Software

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.
Competing Interests: The authors have declared that no competing interests exist.

Genome Biol. 2016 Jun 06;17(1):122. (PMID: 27268795)
Genet Med. 2018 Sep;20(9):1054-1060. (PMID: 29300386)
N Engl J Med. 2015 Dec 10;373(24):2336-2346. (PMID: 26580448)
Bioinformatics. 2019 Mar 1;35(5):865-867. (PMID: 30102335)
Nat Rev Genet. 2011 Sep 27;12(11):745-55. (PMID: 21946919)
Nature. 2016 Aug 17;536(7616):285-91. (PMID: 27535533)
Nucleic Acids Res. 2010 Sep;38(16):e164. (PMID: 20601685)
BMC Med Genomics. 2014 Dec 03;7:64. (PMID: 25466818)
Am J Hum Genet. 2017 Feb 2;100(2):267-280. (PMID: 28132688)
Nucleic Acids Res. 2017 Jan 4;45(D1):D353-D361. (PMID: 27899662)
Genet Med. 2015 May;17(5):405-24. (PMID: 25741868)
Fly (Austin). 2012 Apr-Jun;6(2):80-92. (PMID: 22728672)
Nucleic Acids Res. 2016 Jul 8;44(W1):W90-7. (PMID: 27141961)

Date Created: 20191016 Date Completed: 20200203 Latest Revision: 20200203

20250114

PMC6814239

10.1371/journal.pcbi.1007453

31613886