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Validating Whole Genome Nanopore Sequencing, using Usutu Virus as an Example

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BioNanoAnalyst: a visualisation tool to assess genome assembly quality using BioNano data.

Yuxuan Yuan¹, Philipp E Bayer¹, Armin Scheben¹

¹School of Biological Sciences, the University of Western Australia, Perth, WA, Australia.

BMC Bioinformatics

|July 2, 2017

Summary

BioNanoAnalyst is a new software tool that uses optical mapping data to find errors in genome assemblies. This helps researchers quickly fix mistakes for more accurate genetic analysis.

Keywords:

BioNano Misassembly Optical map Restriction enzyme cut site

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Area of Science:

Genomics
Bioinformatics

Background:

High-quality reference genome assemblies are crucial for accurate genetic studies, but errors and omissions remain common.
Optical mapping technology aids in genome scaffolding and structural variation analysis, complementing DNA sequencing.
Existing tools for identifying misassemblies using optical map data are limited.

Purpose of the Study:

To introduce BioNanoAnalyst, a software package designed to evaluate genome assemblies using optical mapping data.
To provide a user-friendly tool for identifying misassemblies in reference genome sequences.

Main Methods:

BioNanoAnalyst utilizes restriction endonuclease cut sites and optical map data to examine genome assemblies.
The software features a graphical user interface (GUI) for cross-platform accessibility without programming knowledge.
A zoom function enhances visualization, and output is provided in GFF3 format for integration with genome browsers.

Main Results:

BioNanoAnalyst enables comprehensive examination of genome assemblies against optical map data.
The GUI facilitates easy assessment of reference genome sequences.
GFF3 output allows direct visualization of potential assembly errors in genome browsers.

Conclusions:

BioNanoAnalyst is an effective tool for identifying misassemblies in reference genome sequences via optical map data.
The software empowers users to rapidly detect and correct assembly errors, improving downstream analysis accuracy.