MutViz 2.0: visual analysis of somatic mutations and the impact of mutational signatures on selected genomic regions
| Autor: | Eirini Stamoulakatou, Rosario M. Piro, Andrea Gulino |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
AcademicSubjects/SCI01140
0303 health sciences Mutation AcademicSubjects/SCI01060 Somatic cell AcademicSubjects/SCI00030 Context (language use) Promoter Standard Article General Medicine Computational biology Biology AcademicSubjects/SCI01180 medicine.disease_cause DNA binding site 03 medical and health sciences 0302 clinical medicine Germline mutation 030220 oncology & carcinogenesis Ultraviolet light medicine AcademicSubjects/SCI00980 030304 developmental biology Sequence (medicine) |
| Zdroj: | NAR Cancer |
| ISSN: | 2632-8674 |
| DOI: | 10.1093/narcan/zcab012 |
| Popis: | Patterns of somatic single nucleotide variants observed in human cancers vary widely between different tumor types. They depend not only on the activity of diverse mutational processes, such as exposure to ultraviolet light and the deamination of methylated cytosines, but largely also on the sequence content of different genomic regions on which these processes act. With MutViz (http://gmql.eu/mutviz/), we have presented a user-friendly web tool for the identification of mutation enrichments that offers preloaded mutations from public datasets for a variety of cancer types, well organized within an effective database architecture. Somatic mutation patterns can be visually and statistically analyzed within arbitrary sets of small, user-provided genomic regions, such as promoters or collections of transcription factor binding sites. Here, we present MutViz 2.0, a largely extended and consolidated version of the tool: we took into account the immediate (trinucleotide) sequence context of mutations, improved the representation of clinical annotation of tumor samples and devised a method for signature refitting on limited genomic regions to infer the contribution of individual mutational processes to the mutation patterns observed in these regions. We described both the features of MutViz 2.0, concentrating on the novelties, and the substantial re-engineering of the cloud-based architecture. Graphical Abstract Graphical AbstractSimplified workflow of data analysis and visualization with MutViz: Analysis of somatic mutations within user-defined genomic regions for identification and visualization of region-specific mutation characteristics. |
| Databáze: | OpenAIRE |
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