Benchmarking and improving the performance of variant-calling pipelines with RecallME

IF 4.4 3区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS Bioinformatics Pub Date : 2023-12-14 DOI:10.1093/bioinformatics/btad722
G Vozza, E Bonetti, G Tini, V Favalli, G Frige’, G Bucci, S De Summa, M Zanfardino, F Zapelloni, L Mazzarella
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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.
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利用 RecallME 对变体调用管道的性能进行基准测试和改进
动机 全基因组/外显子组测序的稳步发展以及基于 NGS 的新型基因面板的开发,要求对变异调用管道进行持续的测试和验证,并检测与测序相关的问题,以保持其与时俱进性和临床可行性。最先进的工具在计算标准性能指标时是可靠的。然而,目前仍需要一种自动软件来区分生物信息学问题和测序问题,并优化变异调用参数。当前工作的目标是推出 RecallME,这是一个生物信息学套件,可追踪难以检测的变异,如高度重复区域中的插入和缺失,从而为单核苷酸变异和小的插入和缺失提供可达到的最大召回率,并在管道优化过程中为用户提供精确指导。可用性 源代码在 MIT 许可下免费提供,网址是 https://github.com/mazzalab-ieo/recallme RecallME 网络应用程序的网址是 https://translational-oncology-lab.shinyapps.io/recallme/ 要使用 RecallME,用户必须自行获得 ANNOVAR 的许可。补充信息 补充数据可在 Bioinformatics online 上获取。
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来源期刊
Bioinformatics
Bioinformatics 生物-生化研究方法
CiteScore
11.20
自引率
5.20%
发文量
753
审稿时长
2.1 months
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.
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