Title | VariantSurvival: a tool to identify genotype-treatment response. |
Publication Type | Journal Article |
Year of Publication | 2023 |
Authors | Krannich, T, Sarrias, MHerrera, Ben Aribi, H, Shokrof, M, Iacoangeli, A, Al-Chalabi, A, Sedlazeck, FJ, Busby, B, Khleifat, AAl |
Journal | Front Bioinform |
Volume | 3 |
Pagination | 1277923 |
Date Published | 2023 |
ISSN | 2673-7647 |
Abstract | 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. 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 gene. VariantSurvival has a user-friendly and lightweight graphical user interface built on the shiny web application package. |
DOI | 10.3389/fbinf.2023.1277923 |
Alternate Journal | Front Bioinform |
PubMed ID | 37885757 |
PubMed Central ID | PMC10598652 |
Grant List | / WT_ / Wellcome Trust / United Kingdom |