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VariantSurvival: a tool to identify genotype–treatment response

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 clini...

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Autores principales: Krannich, Thomas, Sarrias, Marina Herrera, Ben Aribi, Hiba, Shokrof, Moustafa, Iacoangeli, Alfredo, Al-Chalabi, Ammar, Sedlazeck, Fritz J., Busby, Ben, Al Khleifat, Ahmad
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10598652/
https://www.ncbi.nlm.nih.gov/pubmed/37885757
http://dx.doi.org/10.3389/fbinf.2023.1277923
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author Krannich, Thomas
Sarrias, Marina Herrera
Ben Aribi, Hiba
Shokrof, Moustafa
Iacoangeli, Alfredo
Al-Chalabi, Ammar
Sedlazeck, Fritz J.
Busby, Ben
Al Khleifat, Ahmad
author_facet Krannich, Thomas
Sarrias, Marina Herrera
Ben Aribi, Hiba
Shokrof, Moustafa
Iacoangeli, Alfredo
Al-Chalabi, Ammar
Sedlazeck, Fritz J.
Busby, Ben
Al Khleifat, Ahmad
author_sort Krannich, Thomas
collection PubMed
description 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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spelling pubmed-105986522023-10-26 VariantSurvival: a tool to identify genotype–treatment response Krannich, Thomas Sarrias, Marina Herrera Ben Aribi, Hiba Shokrof, Moustafa Iacoangeli, Alfredo Al-Chalabi, Ammar Sedlazeck, Fritz J. Busby, Ben Al Khleifat, Ahmad Front Bioinform Bioinformatics 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. Frontiers Media S.A. 2023-10-11 /pmc/articles/PMC10598652/ /pubmed/37885757 http://dx.doi.org/10.3389/fbinf.2023.1277923 Text en Copyright © 2023 Krannich, Sarrias, Ben Aribi, Shokrof, Iacoangeli, Al-Chalabi, Sedlazeck, Busby and Al Khleifat. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Bioinformatics
Krannich, Thomas
Sarrias, Marina Herrera
Ben Aribi, Hiba
Shokrof, Moustafa
Iacoangeli, Alfredo
Al-Chalabi, Ammar
Sedlazeck, Fritz J.
Busby, Ben
Al Khleifat, Ahmad
VariantSurvival: a tool to identify genotype–treatment response
title VariantSurvival: a tool to identify genotype–treatment response
title_full VariantSurvival: a tool to identify genotype–treatment response
title_fullStr VariantSurvival: a tool to identify genotype–treatment response
title_full_unstemmed VariantSurvival: a tool to identify genotype–treatment response
title_short VariantSurvival: a tool to identify genotype–treatment response
title_sort variantsurvival: a tool to identify genotype–treatment response
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10598652/
https://www.ncbi.nlm.nih.gov/pubmed/37885757
http://dx.doi.org/10.3389/fbinf.2023.1277923
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