VariantSurvival: a tool to identify genotype–treatment response

Frontiers in Bioinformatics

Bioinformatics

Marina Herrera Sarrias¹  Ben Busby²  Moustafa Shokrof³  Hiba Ben Aribi⁴  Thomas Krannich⁵  Fritz J. Sedlazeck⁶  Ammar Al-Chalabi⁷  Alfredo Iacoangeli⁷  Ahmad Al Khleifat⁷ 

[1] Computational Mathematics Division, Department of Mathematics, Stockholm University, Stockholm, Sweden;DNAnexus, Mountain View, CA, United States;Department of Computer Science, University of California, Davis, CA, United States;Faculty of Science of Tunis, University El Manar, Tunis, Tunisia;Genome Competence Center (MF1), Robert Koch Institute, Berlin, Germany;Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, United States;Maurice Wohl Clinical Neuroscience Institute, King’s College London, London, United Kingdom;

关键词: structural variants;    survival analysis;    clinical trials;    personalized medicine;    Kaplan–Meier;    Cox regression;    R shiny;   

DOI  :  10.3389/fbinf.2023.1277923

 received in 2023-08-15, accepted in 2023-09-22,  发布年份 2023

来源: Frontiers

【 摘 要 】

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.

【 授权许可】

Unknown   
Copyright © 2023 Krannich, Sarrias, Ben Aribi, Shokrof, Iacoangeli, Al-Chalabi, Sedlazeck, Busby and Al Khleifat.