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Var∣Decrypt: a novel and user-friendly tool to explore and prioritize variants in whole-exome sequencing data
BACKGROUND: High-throughput sequencing (HTS) offers unprecedented opportunities for the discovery of causative gene variants in multiple human disorders including cancers, and has revolutionized clinical diagnostics. However, despite more than a decade of use of HTS-based assays, extracting relevant...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10265870/ https://www.ncbi.nlm.nih.gov/pubmed/37312221 http://dx.doi.org/10.1186/s13072-023-00497-4 |
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author | Salma, Mohammad Alaterre, Elina Moreaux, Jérôme Soler, Eric |
author_facet | Salma, Mohammad Alaterre, Elina Moreaux, Jérôme Soler, Eric |
author_sort | Salma, Mohammad |
collection | PubMed |
description | BACKGROUND: High-throughput sequencing (HTS) offers unprecedented opportunities for the discovery of causative gene variants in multiple human disorders including cancers, and has revolutionized clinical diagnostics. However, despite more than a decade of use of HTS-based assays, extracting relevant functional information from whole-exome sequencing (WES) data remains challenging, especially for non-specialists lacking in-depth bioinformatic skills. RESULTS: To address this limitation, we developed Var∣Decrypt, a web-based tool designed to greatly facilitate WES data browsing and analysis. Var∣Decrypt offers a wide range of gene and variant filtering possibilities, clustering and enrichment tools, providing an efficient way to derive patient-specific functional information and to prioritize gene variants for functional analyses. We applied Var∣Decrypt on WES datasets of 10 acute erythroid leukemia patients, a rare and aggressive form of leukemia, and recovered known disease oncogenes in addition to novel putative drivers. We additionally validated the performance of Var∣Decrypt using an independent dataset of ~ 90 multiple myeloma WES, recapitulating the identified deregulated genes and pathways, showing the general applicability and versatility of Var∣Decrypt for WES analysis. CONCLUSION: Despite years of use of WES in human health for diagnosis and discovery of disease drivers, WES data analysis still remains a complex task requiring advanced bioinformatic skills. In that context, there is a need for user-friendly all-in-one dedicated tools for data analysis, to allow biologists and clinicians to extract relevant biological information from patient datasets. Here, we provide Var∣Decrypt (trial version accessible here: https://vardecrypt.com/app/vardecrypt), a simple and intuitive Rshiny application created to fill this gap. Source code and detailed user tutorial are available at https://gitlab.com/mohammadsalma/vardecrypt. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13072-023-00497-4. |
format | Online Article Text |
id | pubmed-10265870 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-102658702023-06-15 Var∣Decrypt: a novel and user-friendly tool to explore and prioritize variants in whole-exome sequencing data Salma, Mohammad Alaterre, Elina Moreaux, Jérôme Soler, Eric Epigenetics Chromatin Methodology BACKGROUND: High-throughput sequencing (HTS) offers unprecedented opportunities for the discovery of causative gene variants in multiple human disorders including cancers, and has revolutionized clinical diagnostics. However, despite more than a decade of use of HTS-based assays, extracting relevant functional information from whole-exome sequencing (WES) data remains challenging, especially for non-specialists lacking in-depth bioinformatic skills. RESULTS: To address this limitation, we developed Var∣Decrypt, a web-based tool designed to greatly facilitate WES data browsing and analysis. Var∣Decrypt offers a wide range of gene and variant filtering possibilities, clustering and enrichment tools, providing an efficient way to derive patient-specific functional information and to prioritize gene variants for functional analyses. We applied Var∣Decrypt on WES datasets of 10 acute erythroid leukemia patients, a rare and aggressive form of leukemia, and recovered known disease oncogenes in addition to novel putative drivers. We additionally validated the performance of Var∣Decrypt using an independent dataset of ~ 90 multiple myeloma WES, recapitulating the identified deregulated genes and pathways, showing the general applicability and versatility of Var∣Decrypt for WES analysis. CONCLUSION: Despite years of use of WES in human health for diagnosis and discovery of disease drivers, WES data analysis still remains a complex task requiring advanced bioinformatic skills. In that context, there is a need for user-friendly all-in-one dedicated tools for data analysis, to allow biologists and clinicians to extract relevant biological information from patient datasets. Here, we provide Var∣Decrypt (trial version accessible here: https://vardecrypt.com/app/vardecrypt), a simple and intuitive Rshiny application created to fill this gap. Source code and detailed user tutorial are available at https://gitlab.com/mohammadsalma/vardecrypt. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13072-023-00497-4. BioMed Central 2023-06-14 /pmc/articles/PMC10265870/ /pubmed/37312221 http://dx.doi.org/10.1186/s13072-023-00497-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Methodology Salma, Mohammad Alaterre, Elina Moreaux, Jérôme Soler, Eric Var∣Decrypt: a novel and user-friendly tool to explore and prioritize variants in whole-exome sequencing data |
title | Var∣Decrypt: a novel and user-friendly tool to explore and prioritize variants in whole-exome sequencing data |
title_full | Var∣Decrypt: a novel and user-friendly tool to explore and prioritize variants in whole-exome sequencing data |
title_fullStr | Var∣Decrypt: a novel and user-friendly tool to explore and prioritize variants in whole-exome sequencing data |
title_full_unstemmed | Var∣Decrypt: a novel and user-friendly tool to explore and prioritize variants in whole-exome sequencing data |
title_short | Var∣Decrypt: a novel and user-friendly tool to explore and prioritize variants in whole-exome sequencing data |
title_sort | var∣decrypt: a novel and user-friendly tool to explore and prioritize variants in whole-exome sequencing data |
topic | Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10265870/ https://www.ncbi.nlm.nih.gov/pubmed/37312221 http://dx.doi.org/10.1186/s13072-023-00497-4 |
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