gmoviz: seamless visualisation of complex genomic variations in GMOs and edited cell lines – An overview

Kathleen Zeglinski, Arthur Hsu, Constantinos Koutsakis and Monther Alhamdoosh

Contents

1 Introduction

gmoviz logo

Genetically modified organisms (GMOs) and cell lines are widely used models in many aspects of biological research. As part of characterising these models, DNA sequencing technology and bioinformatic analyses are used systematically to study their genomes. Large volumes of data are generated and various algorithms are applied to analyse this data, which introduces a challenge with regards to representing all findings in an informative and concise manner. Scientific visualisation can be used to facilitate the explanation of complex genomic editing events such as intergration events, deletions, insertions, etc. However, current visualisation tools tend to focus on numerical data, ignoring the need to visualise editing events on a large yet biologically-relevant scale.

gmoviz is an R package designed to extend traditional bioinformatics workflows used for genomic characterisation with powerful visualisation capabilities based on the Circos (Krzywinski et al. 2009) plotting framework, as implemented in circlize (Gu et al. 2014). gmoviz offers the following key features (summarised in the diagram below):

• Visualise complex structural variations, particularly relating to tandem insertions

• Generate plots in a single function call, or build them piece by piece for finer customisation

• Integration with existing Bioconductor data structures

Flowchart summarising the usage and key functions of gmoviz

1.1 How to read Circos plots

Circos plots have two key components: sectors and tracks. Each sector represents a sequence of interest (such as a chromosome, gene or any other region). Tracks on the other hand are used to display data. For example: