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Revana: a comprehensive tool for regulatory variant analysis and visualization of cancer genomes

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 specia...

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Detalles Bibliográficos
Autores principales: Ulrich, Elias, Pfister, Stefan M, Jäger, Natalie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9822537/
https://www.ncbi.nlm.nih.gov/pubmed/36576005
http://dx.doi.org/10.1093/bioinformatics/btac831
Descripción
Sumario: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 <https://github.com/KiTZ-Heidelberg/revana>. Sample results can be viewed under <https://github.com/KiTZ-Heidelberg/revana-demo-report> and a short walkthrough is available under <https://github.com/KiTZ-Heidelberg/revana-demo-data>. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.