LayerCake: a tool for the visual comparison of viral deep sequencing data

Area of Science:

• Genomics
• Virology
• Bioinformatics

Background:

• Next-generation sequencing (NGS) enables detailed examination of viral populations.
• Analyzing sequence variability is crucial for understanding viral population structures and biological insights.
• Current NGS tools face challenges in visualizing sequence variation, coverage depth, and quality scores simultaneously across large genomic regions.

Purpose of the Study:

• To introduce LayerCake, a novel visualization tool for rapid analysis of viral NGS data.
• To address the visualization challenges in displaying complex viral genomic variation.
• To provide a customizable framework for identifying patterns in viral population data.

Main Methods:

• LayerCake is a self-contained, cross-platform visualization tool.
• Developed using the Processing framework for Java.
• Enables simultaneous visualization of variation, coverage depth, and quality scores.

Main Results:

• LayerCake facilitates the rapid analysis of variation in viral NGS data.
• Allows simultaneous visualization of multiple viral populations across entire genomes.
• Successfully deployed for diverse genomics datasets, highlighting pertinent variation patterns.

Conclusions:

• LayerCake offers a powerful solution for visualizing complex viral NGS data.
• Enhances the ability to study viral population dynamics and genomic variation.
• A valuable tool for researchers in virology and genomics.