G Vozza, E Bonetti, G Tini, V Favalli, G Frige’, G Bucci, S De Summa, M Zanfardino, F Zapelloni, L Mazzarella
{"title":"Benchmarking and improving the performance of variant-calling pipelines with RecallME","authors":"G Vozza, E Bonetti, G Tini, V Favalli, G Frige’, G Bucci, S De Summa, M Zanfardino, F Zapelloni, L Mazzarella","doi":"10.1093/bioinformatics/btad722","DOIUrl":null,"url":null,"abstract":"Motivation The steady increment of Whole Genome/Exome sequencing and the development of novel NGS-based gene panels requires continuous testing and validation of variant calling pipelines and the detection of sequencing-related issues to be maintained up-to-date and feasible for the clinical settings. State of the art tools are reliable when used to compute standard performance metrics. However, the need for an automated software to discriminate between bioinformatic and sequencing issues and to optimize variant calling parameters remains unmet. The aim of the current work is to present RecallME, a bioinformatic suite that tracks down difficult-to-detect variants as insertions and deletions in highly repetitive regions, thus providing the maximum reachable recall for both single nucleotide variants and small insertion and deletions and to precisely guide the user in the pipeline optimization process. Availability Source code is freely available under MIT license at https://github.com/mazzalab-ieo/recallme RecallME web application is available at https://translational-oncology-lab.shinyapps.io/recallme/ To use RecallME, users must obtain a license for ANNOVAR by themselves. Supplementary information Supplementary data are available at Bioinformatics online.","PeriodicalId":8903,"journal":{"name":"Bioinformatics","volume":null,"pages":null},"PeriodicalIF":4.4000,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bioinformatics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1093/bioinformatics/btad722","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
Motivation The steady increment of Whole Genome/Exome sequencing and the development of novel NGS-based gene panels requires continuous testing and validation of variant calling pipelines and the detection of sequencing-related issues to be maintained up-to-date and feasible for the clinical settings. State of the art tools are reliable when used to compute standard performance metrics. However, the need for an automated software to discriminate between bioinformatic and sequencing issues and to optimize variant calling parameters remains unmet. The aim of the current work is to present RecallME, a bioinformatic suite that tracks down difficult-to-detect variants as insertions and deletions in highly repetitive regions, thus providing the maximum reachable recall for both single nucleotide variants and small insertion and deletions and to precisely guide the user in the pipeline optimization process. Availability Source code is freely available under MIT license at https://github.com/mazzalab-ieo/recallme RecallME web application is available at https://translational-oncology-lab.shinyapps.io/recallme/ To use RecallME, users must obtain a license for ANNOVAR by themselves. Supplementary information Supplementary data are available at Bioinformatics online.
期刊介绍:
The leading journal in its field, Bioinformatics publishes the highest quality scientific papers and review articles of interest to academic and industrial researchers. Its main focus is on new developments in genome bioinformatics and computational biology. Two distinct sections within the journal - Discovery Notes and Application Notes- focus on shorter papers; the former reporting biologically interesting discoveries using computational methods, the latter exploring the applications used for experiments.