altAFplotter: a web app for reliable UPD detection in NGS diagnostics

IF 2.9 3区生物学 Q2 BIOCHEMICAL RESEARCH METHODS

BMC Bioinformatics Pub Date : 2024-09-12 DOI:10.1186/s12859-024-05922-3

Maximilian Radtke, Johanna Moch, Julia Hentschel, Isabell Schumann

引用次数: 0

Abstract

The detection of uniparental disomies (the inheritance of both chromosome homologues from a single parent, UPDs) is not part of most standard or commercial NGS-pipelines in human genetics and thus a common gap in NGS diagnostics. To address this we developed a tool for UPD-detection based on panel or exome data which is easy to use and publicly available. The app is freely available at https://altafplotter.uni-leipzig.de/ and implemented in Python, using the Streamlit framework for data science web apps. It utilizes bcftools and tabix for processing vcf files. The source code is available at https://github.com/HUGLeipzig/altafplotter and can be used to host your own instance of the tool. We believe the app to be a great benefit for research and diagnostic labs, which struggle identifying and interpreting UPDs in their NGS diagnostic setup. The information provided allows a quick interpretation of the results and thus is suitable for usage in a high throughput manner by clinicians and biologists.

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altAFplotter：用于 NGS 诊断中可靠 UPD 检测的网络应用程序

人类遗传学中的大多数标准或商业 NGS 管线都不包括单亲遗传病（单亲染色体同源染色体的遗传，UPDs）的检测，因此这是 NGS 诊断中的一个常见缺陷。为了解决这个问题，我们开发了一个基于面板或外显子组数据的 UPD 检测工具，该工具易于使用，并可公开获取。该应用程序可在 https://altafplotter.uni-leipzig.de/ 免费获取，使用 Python 实现，并使用了用于数据科学网络应用程序的 Streamlit 框架。它利用 bcftools 和 tabix 处理 vcf 文件。源代码可从 https://github.com/HUGLeipzig/altafplotter 获取，您可以用它来托管自己的工具实例。我们相信，该应用程序对研究和诊断实验室大有裨益，因为他们在 NGS 诊断设置中很难识别和解释 UPD。所提供的信息可以快速解读结果，因此适合临床医生和生物学家以高通量的方式使用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

BMC Bioinformatics 生物-生化研究方法

CiteScore

5.70

自引率

3.30%

发文量

506

审稿时长

4.3 months

期刊介绍： BMC Bioinformatics is an open access, peer-reviewed journal that considers articles on all aspects of the development, testing and novel application of computational and statistical methods for the modeling and analysis of all kinds of biological data, as well as other areas of computational biology. BMC Bioinformatics is part of the BMC series which publishes subject-specific journals focused on the needs of individual research communities across all areas of biology and medicine. We offer an efficient, fair and friendly peer review service, and are committed to publishing all sound science, provided that there is some advance in knowledge presented by the work.