VariantSurvival: a tool to identify genotype-treatment response.

IF 2.8 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY

Frontiers in bioinformatics Pub Date : 2023-10-11 eCollection Date: 2023-01-01 DOI:10.3389/fbinf.2023.1277923

Thomas Krannich, Marina Herrera Sarrias, Hiba Ben Aribi, Moustafa Shokrof, Alfredo Iacoangeli, Ammar Al-Chalabi, Fritz J Sedlazeck, Ben Busby, Ahmad Al Khleifat

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引用次数: 0

Abstract

Motivation: For a number of neurological diseases, such as Alzheimer's disease, amyotrophic lateral sclerosis, and many others, certain genes are known to be involved in the disease mechanism. A common question is whether a structural variant in any such gene may be related to drug response in clinical trials and how this relationship can contribute to the lifecycle of drug development. Results: To this end, we introduce VariantSurvival, a tool that identifies changes in survival relative to structural variants within target genes. VariantSurvival matches annotated structural variants with genes that are clinically relevant to neurological diseases. A Cox regression model determines the change in survival between the placebo and clinical trial groups with respect to the number of structural variants in the drug target genes. We demonstrate the functionality of our approach with the exemplary case of the SETX gene. VariantSurvival has a user-friendly and lightweight graphical user interface built on the shiny web application package.

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VariantSurvival：一种识别基因型治疗反应的工具。

动机：对于许多神经系统疾病，如阿尔茨海默病、肌萎缩侧索硬化症和许多其他疾病，已知某些基因与疾病机制有关。一个常见的问题是，任何此类基因的结构变异是否与临床试验中的药物反应有关，以及这种关系如何有助于药物开发的生命周期。结果：为此，我们引入了VariantSurvival，这是一种识别存活率相对于靶基因结构变异变化的工具。VariantSurvival将注释的结构变体与临床上与神经疾病相关的基因进行匹配。Cox回归模型确定了安慰剂组和临床试验组之间相对于药物靶基因结构变异数量的生存率变化。我们用SETX基因的例子来证明我们的方法的功能。VariantSurvival在闪亮的web应用程序包上构建了一个用户友好、轻量级的图形用户界面。

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

Frontiers in bioinformatics

CiteScore

2.60

自引率

0.00%

发文量