Ontology highlight
ABSTRACT: Motivation
As non-coding driver mutations move more into the focus of cancer research, a comprehensive and easy-to-use software solution for regulatory variant analysis and data visualization is highly relevant. The interpretation of regulatory variants in large tumor genome cohorts requires specialized analysis and visualization of multiple layers of data, including for example breakpoints of structural variants, enhancer elements and additional available gene locus annotation, in the context of changes in gene expression.Results
We introduce a user-friendly tool, Revana (REgulatory Variant ANAlysis), that can aggregate and visually represent regulatory variants from cancer genomes in a gene-centric manner. It requires whole-genome and RNA sequencing data of a cohort of tumor samples and creates interactive HTML reports summarizing the most important regulatory events.Availability and implementation
Revana is implemented in R and JavaScript. It is available for download as an R package under Supplementary information
Supplementary data are available at Bioinformatics online.
SUBMITTER: Ulrich E
PROVIDER: S-EPMC9822537 | biostudies-literature | 2023 Jan
REPOSITORIES: biostudies-literature
Ulrich Elias E Pfister Stefan M SM Jäger Natalie N
Bioinformatics (Oxford, England) 20230101 1
<h4>Motivation</h4>As non-coding driver mutations move more into the focus of cancer research, a comprehensive and easy-to-use software solution for regulatory variant analysis and data visualization is highly relevant. The interpretation of regulatory variants in large tumor genome cohorts requires specialized analysis and visualization of multiple layers of data, including for example breakpoints of structural variants, enhancer elements and additional available gene locus annotation, in the c ...[more]