PanGraphViewer -- show panenome graphs in an easy way

Table of Contents

• Versions and installation
• Files accepted
• Start the program
• Run the program
• Q&A:
  • Operating system
  • Minimum computational resource needed
  • Which application should I use
  • How to use the application
  • Backbone sample
  • Colors shown in the graph
  • Type of graphs
  • Shapes shown in the graph
  • Different variations
  • Pros and cons of the application

Please read the information below carefully to have a better experience in using PanGraphViewer.

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Versions and installation

Here we provide two application versions:

● Desktop-based application
● Web-based application

Overall, Python3.6 or above is needed to run this software. We highly recommend users using miniconda3 to run this program.

Users can refer to the Installation at the Wiki page to install the tool.

To futher assist the installation and use, we have provided two Youtube videos to guild users to use this tool.

On Windows

Users may refer to https://youtu.be/YrltzD8R5Io

On Other operating systems

Users may refer to https://youtu.be/tpLjcOz2E4U

Files accepted

PanGraphViewer accepts different pangenome graph formats, including rGFA, GFA_v1 and VCF.

PanGraphViewer can also accept genome annotation files, such as BED, GTF/GFF files.

Before using this tool, users may refer to data formats to prepare the files and then run the program.

Start the program

Users may refer to start the program to open the user interface.

Run the program

Users may refer to the Manual to run the program.

Q&A:

Operating system

• For the desktop-based application, it has been optimized on

   Windows 10
   macOS Big Sur, macOS Monterey, Ubuntu 18.04.5 and Ubuntu 20.04
  

  For other operating systems or equivalents, the tool may also work. However, on older operating systems, such as Ubuntu 16.04, PyQtWebEngine may not work properly.

• For the web-based version, we suggest running in Linux or macOS environment. If users want to run on Windows systems, Windows 10 or above is recommended.

  Users can also use docker to run the web-based version (see the instruction here). However, WSL is needed to run the docker version on Windows 10 or above.

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Minimum computational resource needed

Memory:  2Gb
Threads: 2

Users can adjust the RAM depending on the size of the pangenome graph.

From our preliminary tests, it seems 8Gb RAM would be sufficient to view most graphs.

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Which application should I use

• Depending on the purpose and preference, users can select either the desktop-based application or the web-based application. Basically, the desktop-based application is more intendedly designed for single users who have little computer science background. This application allows users to easily browse the graph by simply clicking the buttons.

• By contrast, the web-based application is more suitable for multiple users who have a shared Linux server/cluster. The administrator can easily deploy the application on a server and set accounts for different users to access this tool in any device with a web browser and internet connection. Users can also easily share their files or results on the server. While the web-based application is not limited to a server, it can be installed locally in case that the desktop-based version fails in installation.

• Most of the functions in the desktop-based version and the web-based version are the same. However, there are some differences. First, to make the response time acceptable, in the web-based application, we only use cytoscape.js to draw graphs. In contrast, vis.js and cytoscape.js are used in the desktop-based application to draw graphs depending on how many nodes a user wants to browse. By default, 200 nodes are allowed to show in vis.js-based graph. Users can change this setting in Settings--> Graph Modification to decide either using vis.js or cytoscape.js.

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Backbone sample

• The backbone sample is the one used as the main sequence provider to produce the pangenome graph or the reference sample to produce the VCF file.
• In a pangenome graph, most of the nodes are from the backbone sample (shared by all) with some nodes (variations) from other samples.

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Colors shown in the graph

• Each sample uses one particular colour and the most frequent colour is the one used for the backbone sample.
• By default, the colours are randomly selected by the program from a designed colour palette.
• Users can customise the color scheme in the config_default.ini or config.ini file to fix the colors for samples (number of colors = number of samples).
• In the legend, users can check the color used for each sample.

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Type of graphs

• We provide two kinds of graph plots in the desktop-based application to achieve a good performance and visualisation. By default, if the number of checked nodes <= 200, vis.js based graph will show. Otherwise, a cytoscape.js based graph will show. Users can change the settings in the desktop-based application to set the type of plot.
• In the web-based application, cytoscape.js based graph is provided.

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Shapes shown in the graph

• If users use a VCF file to show variation-based graphs, we use different nodes shapes to represent different kinds of variants. For instance, in the default settings for the vis.js-based graph,

   o represents SNP
   △ represents deletion
   ▽ represents insertion 
   ☷ represents duplication 
   text shows inversion
   ☆ represents translocation
  

Users can change the corresponding settings to select preferred node shapes to represent different variations on the desktop-based application.

In the legend, users can check the shapes used for representing different variations.

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Different variations

• If users use a VCF file to generate a graph genome, when moving the mouse to the graph node, the program will show the variation types automatically, such as

   SNP:   single nucleotide polymorphism
   INS:   insertion
   DEL:   deletion
   INV:   inversion 
   DUP:   duplication
   TRANS: translocation
  

The corresponding nodes from the backbone sample will also be linked and shown.

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Pros and cons of the application

There are some pros and cons of this application. We list some here for your reference

Pros

• can directly plot a subgraph of interest from a pangenome graph
• can specify coordinates to check subgraphs and nodes
• can browse graphs from a VCF file
• can show variations, particularly structural variations if the graph is generated from a VCF file
• can check nodes falling in a gene model region and alter users if the nodes have the chance to change the function of the gene model in some individuals
• can show the origin of particular nodes in a pangenome graph
• Computational resource-efficient in using this tool

Cons

• When checking hundreds or thousands of nodes in vis.js-based graph, the nodes may cluster together in the plot which may be difficult to interpret [Third-party javascript layout problem; in this case we suggest switching to cytoscape.js-based graphs in Settings]
• Some python libraries used, such as 'PyQtWebEngine' may not be compatible with all operating systems if using the desktop-based application [Third-party library problem; in this case users may use the web browser-based version]
• Remote accessing to the desktop-based application may confront plotting problems, particularly when using macOS system remote accessing to the Linux system [Selection problem; in this case users may want to install the desktop-based application locally or use the web browser-based version]
• In macOS, if users use the web browser-based application, the hover for nodes cannot show properly in Safari [Browser problem; in this case users may use Chrome or Microsoft Edge]
• May not be able to efficiently display a graph containing more than 20,000 nodes [Render problem - may render slowly or even crash in the display canvas. This is a problem inherited from the third-party javascript we used. In this case, users may want to adjust the plotting region to avoid this problem]

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Enjoy using panGraphViewer!