Difference between revisions of "JBrowse 2 Tutorial PAG 2022"

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Revision as of 21:13, 28 December 2021

This is very much a draft version of the PAG 2022 tutorial, using the JBrowse 1 tutorial as a template.

This tutorial assumes a VirtualBox Ubuntu 18.04 (LTS) instance with the tutorial bundle zip file, also available on Amazon S3: JBrowse PAG 2020.ova (about 4GB) or PAG_2020_JBrowse.zip (about 36MB) for just the JBrowse source and data files for this tutorial.

Prerequisites

Prerequisites are installed by JBrowse automatically. A few things may fail to install (like legacy support for wiggle files), but that doesn't matter.

Make sure you can copy/paste from the wiki.

It's also very useful to know how to tab-complete in the shell.

It's probably a good idea to use a browser like Chrome or Firefox that has the ability to turn off caching while working on this tutorial. To do this in Chrome, with the browser open to the JBrowse page you're working on, select Developer->Javascript Console from the View menu. In the console, click the "gear" icon (settings) and check the box labeled "Disable Cache".

A few basic packages were installed before JBrowse via apt-get:

 sudo apt-get install build-essential zlib1g-dev apache2 curl

Also, a few items were installed that aren't needed for this tutorial but would be necessary if you wanted to add plugins (git and NodeJS):

 curl -sL https://deb.nodesource.com/setup_13.x | sudo -E bash -
 sudo apt-get install -y nodejs
 sudo apt-get install git

JBrowse Introduction

How and why JBrowse is different from most other web-based genome browsers, including GBrowse.

More detail: paper

JBrowse presentation

Setting up JBrowse

Launch new session.png

Open new sequence.png

Add second sequence.png

Assembly manager.png

View types-pick dotplot.png

Assemblies in dotplot.png

Dotplot.png

Zoom-open synteny.png

Dotplot and synteny.png

Add track.png

Gene track data url.png

Change track name to gene.png

Zoomed out loaded tracks.png

Zoomed in synteny with genes.png


Getting JBrowse

A Short Detour for GFF

GFF (Generic Feature Format) is a very commonly used text format for describing features that exist on sequences. We'll head off to that page to talk about it a bit.

Features from a directory of files

Here, we'll use the Bio::DB::SeqFeature::Store adaptor in "memory" mode to read a directory of files. There are adaptors available for use with many other databases, such as Chado and Bio::DB::GFF.

Config file: pythium-1.conf

{
  "description": "PAG 2017 P. ultima Example",
  "db_adaptor": "Bio::DB::SeqFeature::Store",
  "db_args" : {
      "-adaptor" : "memory",
      "-dir" : ".."
   },
...

Specify reference sequences

Load Feature Data

Index feature names

Features from GFF3 or BED files

Quantitative data

Changing the way tracks look

Using Plugins

Other links