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XVCF: Exquisite visualization of VCF data from genomic experiments
Ghaida Almuneef1, Abdulrhman Aljouie2, Yahya Bokhari3
1Artificial Intelligence and Bioinformatics Department, King Abdullah International Medical Research Center, Riyadh, Saudi Arabia; King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia.
Background:
High-throughput genomic analyses of germline and cancer genomes facilitate the identification of causal and actionable genetic variants. The recent advances in next-generation sequencing technology generated large-scale genomic and/or multi-omics dataset. Due to huge volume of data, scientists are facing challenges in visualizing, and interpreting the data. Currently available tools to visualize genetic variants from VCF files are not very user-friendly as most of them require knowledge of command line tools or scripts to install and run those software. Therefore, graphical user interface based tools or software are needed to summarize and visualize the VCF data.
Methods:
We have developed a Shiny App, interactive tool using the R programming language that utilizes existing R packages like "vcfR" and "maftools" to visualize and generate quality control metrics for genetic data. Our tool is powered by Shiny, making it easier to summarize and visualize genomic data using a GUI.
Results:
XVCF has been developed for the summarization and visualization of genomic variation data. The tool offers an easy and friendly interface, allowing users to perform data loading, summarization, and visualization interactively. XVCF extract useful information such as read depth, mapping quality, genotype, quality control summary, and allele frequency from unannotated data. In the second module of XVCF, the cancer genomic data is analyzed using "maftools" to produce oncoplot, lollipop plot, gene summary, etc. XVCF is available for free download from https://github.com/rashidma/XVCF. Being a shiny R package, XVCF can be installed across different operating systems and utilize different computer hardware configurations.
Short Abstract:
Visualizing genomic data has always been challenging. Existing tools/software seem to be difficult to use due to lack of technical computer programming knowledge. We offer XVCF to visualize and/or summarize genomic data at a greater ease due to its graphical user interface and powerful cross-platform R shiny framework.
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