SynVisio

An Interactive Multiscale Synteny Visualization Tool for McScanX.

How does it work ?

SynVisio lets you explore the results of McScanX a popular synteny and collinearity detection toolkit and generate publication ready images.

SynVisio requires two files to run:

  • The simplified gff file that was used as an input for a McScanX query.
  • The collinearity file generated as an output by McScanX for the same input query.
  • Optional track file in bedgraph format to annotate the generated charts.

SynVisio offers different types of visualizations such as Linear Parallel plots, Hive plots, Stacked Parallel Plots and Dot plots. Users can configure the type of plots required and then choose the source and the target chromosomes that need to be mapped. Users also have option to download the generated visualizations in publication ready SVG or PNG formats.

SynVisio works best when opened in Google chrome.

Publication Citation

Venkat Bandi, and Carl Gutwin. 2020. Interactive Exploration of Genomic Conservation. In Proceedings of the 46th Graphics Interface Conference on Proceedings of Graphics Interface 2020 (GI’20). Canadian Human-Computer Communications Society, Waterloo, CAN.

Visualizations generated by SynVisio

System Demonstration

Use the following links for tutorial videos on using SynVisio. They might be outdated but will be updated shortly. Meanwhile you can drop a mail to venkat.bandi@usask.ca for help with any particular features.

Basic Dashboard Demo

Multi Analysis Hive plot

Visualizing additional tracks

Detailed description of all features in SynVisio

Sample Playground

We are working on adding several new features to this tool. We have loaded up some sample files below that you can play around with :

Learn more

This tool was developed at the Human Computer Interaction Lab at the University of Saskatchewan, Canada to assist genome researchers at the Plant Phenotyping and Imaging Research Centre, Canada (P2IRC). This tool is part of series of systems that are currently under development as part of the Theme 3 (Computational Informatics of Crop Phenotype Data) of the P2IRC project.

Contributions are made by:

Project Lead - Carl Gutwin

System Architect - Venkat Bandi

Research Collaborators - Isobel Parkin, Andrew Sharpe, Kirstin Bett, Larissa Ramsay and Kevin Koh