Department of Medical and Surgical Sciences, University of Bologna, Bologna 40138, Italy.
Medical Genetics Unit, Sant'Orsola-Malpighi University Hospital, via Massarenti 9, Bologna 40138, Italy.
Bioinformatics. 2021 May 5;37(5):723-725. doi: 10.1093/bioinformatics/btaa730.
Next-generation sequencing is increasingly adopted in the clinical practice largely thanks to concurrent advancements in bioinformatic tools for variant detection and annotation. However, the need to assess sequencing quality at the base-pair level still poses challenges for diagnostic accuracy. One of the most popular quality parameters is the percentage of targeted bases characterized by low depth of coverage (DoC). These regions potentially 'hide' clinically relevant variants, but no annotation is usually returned with them. However, visualizing low-DoC data with their potential functional and clinical consequences may be useful to prioritize inspection of specific regions before re-sequencing all coverage gaps or making assertions about completeness of the diagnostic test. To meet this need, we have developed unCOVERApp, an interactive application for graphical inspection and clinical annotation of low-DoC genomic regions containing genes.
unCOVERApp interactive plots allow to display gene sequence coverage down to the base-pair level, and functional and clinical annotations of sites below a user-defined DoC threshold can be downloaded in a user-friendly spreadsheet format. Moreover, unCOVERApp provides a simple statistical framework to evaluate if DoC is sufficient for the detection of somatic variants. A maximum credible allele frequency calculator is also available allowing users to set allele frequency cut-offs based on assumptions about the genetic architecture of the disease. In conclusion, unCOVERApp is an original tool designed to identify sites of potential clinical interest that may be 'hidden' in diagnostic sequencing data.
unCOVERApp is a free application developed with Shiny packages and available in GitHub (https://github.com/Manuelaio/uncoverappLib).
Supplementary data are available at Bioinformatics online.
由于用于变异检测和注释的生物信息学工具的同步进展,下一代测序技术在临床实践中越来越多地被采用。然而,在碱基对水平评估测序质量仍然对诊断准确性提出了挑战。最受欢迎的质量参数之一是低深度覆盖(DoC)特征的靶向碱基的百分比。这些区域可能“隐藏”了临床相关的变异,但通常不会返回它们的注释。然而,可视化具有潜在功能和临床后果的低 DoC 数据可能有助于在重新测序所有覆盖缺口之前优先检查特定区域,或者对诊断测试的完整性做出断言。为了满足这一需求,我们开发了 unCOVERApp,这是一个用于交互式检查和注释包含基因的低 DoC 基因组区域的应用程序。
unCOVERApp 交互式图可以显示基因序列覆盖度,直至碱基对水平,并且可以以下载用户定义的 DoC 阈值以下的站点的功能和临床注释的用户友好的电子表格格式。此外,unCOVERApp 提供了一个简单的统计框架来评估 DoC 是否足以检测体细胞变异。还提供了最大可信等位基因频率计算器,允许用户根据疾病的遗传结构假设设置等位基因频率截止值。总之,unCOVERApp 是一种原始工具,旨在识别可能隐藏在诊断测序数据中的潜在临床关注位点。
unCOVERApp 是一个免费的应用程序,使用 Shiny 包开发,并可在 GitHub 上获得(https://github.com/Manuelaio/uncoverappLib)。
补充数据可在 Bioinformatics 在线获得。