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

TITLE=VariantSurvival: a tool to identify genotype–treatment response

JOURNAL=Frontiers in Bioinformatics

VOLUME=3

YEAR=2023

URL=https://www.frontiersin.org/journals/bioinformatics/articles/10.3389/fbinf.2023.1277923

DOI=10.3389/fbinf.2023.1277923

ISSN=2673-7647

ABSTRACT=<p><bold>Motivation:</bold> 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.</p><p><bold>Results:</bold> 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 <italic>SETX</italic> gene. VariantSurvival has a user-friendly and lightweight graphical user interface built on the shiny web application package.</p>