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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
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Oviz-Bio: a web-based platform for interactive cancer genomics data visualization.

Wenlong Jia1, Hechen Li1, Shiying Li1

  • 1Department of Computer Science, City University of Hong Kong, Kowloon TongĀ 999077, Hong Kong.

Nucleic Acids Research
|May 12, 2020
PubMed
Summary
This summary is machine-generated.

Oviz-Bio offers interactive, web-based cancer genomics data visualization, simplifying the exploration of complex genetic mutations. This platform enables researchers to easily generate high-quality diagrams from cancer genome research.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Cancer Research

Background:

  • Cancer genome research generates vast amounts of data requiring effective knowledge sharing.
  • Current static visualization methods often demand significant coding expertise, limiting accessibility.
  • There is a need for intuitive tools to explore complex cancer genomics data.

Purpose of the Study:

  • To introduce Oviz-Bio, a novel web-based platform for interactive cancer genomics data visualization.
  • To provide researchers with an accessible tool for exploring and exporting high-quality genomic visualizations.
  • To support a wide array of cancer mutation types and multi-layered data analysis.

Main Methods:

  • Development of a web-based platform, Oviz-Bio, featuring real-time, interactive visualizations.
  • Integration of diverse visualization types for small-scale mutations, copy number variations, structural variations, fusion genes, and oncovirus integrations.
  • Implementation of a landscape view for cohort-level, multi-layered data investigation.

Main Results:

  • Oviz-Bio successfully provides interactive and real-time visualizations for various cancer genomics data types.
  • The platform supports exploration and export of high-quality diagrams for small-scale mutations, copy number variations, structural variations, fusion genes, and oncovirus integrations.
  • A landscape view enables comprehensive analysis of multi-layered data across sample cohorts.

Conclusions:

  • Oviz-Bio significantly enhances the accessibility and interactivity of cancer genomics data visualization.
  • The platform empowers researchers to explore complex genetic data without extensive coding knowledge.
  • Oviz-Bio is freely available, promoting broader adoption and knowledge sharing in cancer research.