This JBrowse tutorial was presented by Robert Buels at the 2013 GMOD Summer School in July 2013 using JBrowse 1.9.8.
This tutorial uses the AWS AMI ami-d2c8b1bb named 2013 GMOD start day 3 in the US-East region.
These have already been set up on the VM image.
Optional, for generating images from Wiggle files:
Optional, for BAM files (setup.sh tries to install these for you in
the JBrowse directory):
Other prerequisites are installed by JBrowse automatically.
This is how they were installed: (don’t do this yourself)
sudo apt-get install libpng12-0 libpng12-dev build-essential libncurses5-dev
Make sure you can copy/paste from the wiki.
It’s also very useful to know how to tab-complete in the shell.
How and why JBrowse is different from most other web-based genome browsers, including GBrowse.
More detail: paper
cd /var/www
sudo mkdir jbrowse_demo
sudo chown ubuntu.ubuntu jbrowse_demo
cd jbrowse_demo
wget http://jbrowse.org/info/GMOD_Jul_2013/GMOD_Summer_School_2013_JBrowse.zip
unzip GMOD_Summer_School_2013_JBrowse.zip
cd GMOD_Summer_School_2013_JBrowse/
unzip JBrowse-1.9.8.zip
mv JBrowse-1.9.8 jbrowse
setup.sh to configure this copy of JBrowsecd jbrowse
./setup.sh
Visit in web browser:
http://ec2-##-##-##-##.compute-1.amazonaws.com/jbrowse_demo/GMOD_Summer_School_2013_JBrowse/jbrowse/index.html
You should see a “Congratulations” page.
There are four basic steps to setting up an instance of JBrowse:
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": "GMOD Summer School 2013 P. ultima Example",
"db_adaptor": "Bio::DB::SeqFeature::Store",
"db_args" : {
"-adaptor" : "memory",
"-dir" : ".."
},
...
The first script to run is bin/prepare-refseqs.pl; that script is the
way you tell JBrowse about what your reference sequences are. Running
bin/prepare-refseqs.pl also sets up the “DNA” track.
Run this from within the jbrowse directory (you could run it
elsewhere, but you’d have to explicitly specify the location of the data
directory on the command line).
cd /var/www/jbrowse_demo/GMOD_Summer_School_2013_JBrowse/jbrowse
bin/prepare-refseqs.pl --gff ../scf1117875582023.gff
Refresh it in your web browser, you should new see the JBrowse UI and a sequence track, which will show you the DNA base pairs if you zoom in far enough.
Next, we’ll use biodb-to-json.pl to get feature data out of the
database and turn it into JSON data that the
web browser can use.
In this case, we have specified all of our track configurations in
pythium-1.conf.
...
"TRACK DEFAULTS": {
"class": "feature"
},
"tracks": [
{
"track": "Genes",
"key": "Genes",
"feature": ["mRNA"],
"autocomplete": "all",
"class": "transcript",
"subfeature_classes" : {
"CDS" : "transcript-CDS",
"UTR" : "transcript-UTR"
}
},
...
]
track specifies the track identifier (a unique name for the track, for
the software to use). This should be just letters and numbers and - and
_ characters; using other characters makes things less convenient.
key specifies a human-friendly name for the track, which can use any
characters you want.
feature gives a list of feature types to include in the track.
autocomplete including this setting makes the features in the track
searchable.
urltemplate specifies a URL pattern that you can use to link genomic
features to specific web pages.
class specifies the CSS class that
describes how the feature should look.
For this particular track, I’ve specified the transcript feature
class.
Run the bin/biodb-to-json.pl script with this config file to format
this track, and the others in the file:
bin/biodb-to-json.pl --conf ../pythium-1.conf
Refresh JBrowse in your web browser. You should now see a bunch of annotation tracks.
When you generate JSON for a track, if you specify "autocomplete" then
a listing of all of the feature names from that track (along with
feature locations) will also be generated and used to provide feature
searching and autocompletion.
The bin/generate-names.pl script collects those lists of names from
all the tracks and combines them into one big tree that the client uses
to search.
bin/generate-names.pl -v
Visit in web browser, try typing a feature name, such as maker-scf1117875582023-snap-gene-0.26-mRNA-1. Notice that JBrowse tries to auto-complete what you type.
We’re going to add a couple more tracks that come from a flat file,
repeats.gff. To get feature data from flat files into JBrowse, we use
flatfile-to-json.pl.
bin/flatfile-to-json.pl --trackLabel repeatmasker \
--type match:repeatmasker --key RepeatMasker \
--className generic_parent \
--subfeatureClasses '{"match_part" : "feature"}' --gff ../repeats.gff
bin/flatfile-to-json.pl --trackLabel repeatrunner \
--type protein_match:repeatrunner \
--key RepeatRunner --className generic_parent \
--subfeatureClasses '{"match_part" : "feature"}' --gff ../repeats.gff
Visit in web browser; you should see the two new RepeatMasker and RepeatRunner tracks.
JBrowse can display alignments directly from a BAM file on your web server. Simply place the BAM file in a directory accessible to your web server, and add a snippet of configuration to JBrowse to add the track, similar to:
{
"label" : "bam_alignments",
"key" : "BAM alignments",
"storeClass" : "JBrowse/Store/SeqFeature/BAM",
"urlTemplate" : "../../simulated-sorted.bam",
"type" : "Alignments2"
}
This can be added by either editing the data/trackList.json file with
a text editor, or by running something like this at the command line to
inject the track configuration:
echo '{
"label" : "bam_alignments",
"key" : "BAM alignments",
"storeClass" : "JBrowse/Store/SeqFeature/BAM",
"urlTemplate" : "../../simulated-sorted.bam",
"type" : "Alignments2"
}' | bin/add-track-json.pl data/trackList.json
{
"label" : "bam_coverage",
"key" : "BAM Coverage",
"storeClass" : "JBrowse/Store/SeqFeature/BAM",
"urlTemplate" : "../../simulated-sorted.bam",
"type" : "SNPCoverage"
}
JBrowse can display quantitative data directly from a BigWig file on your web server. Simply place the BigWig file in a directory accessible to your web server, and add a snippet of configuration to JBrowse to add the track, similar to:
{
"label" : "bigwig_bam_coverage",
"key" : "BigWig - BAM coverage",
"storeClass" : "BigWig",
"urlTemplate" : "../../simulated-sorted.bam.coverage.bw",
"type" : "JBrowse/View/Track/Wiggle/XYPlot",
"variance_band" : true
}
This can be added by either editing the data/trackList.json file with
a text editor, or by running something like this at the command line to
inject the track configuration:
echo ' {
"label" : "bam_coverage",
"key" : "BAM coverage",
"storeClass" : "BigWig",
"urlTemplate" : "../../simulated-sorted.bam.coverage.bw",
"type" : "JBrowse/View/Track/Wiggle/XYPlot",
"variance_band" : true
} ' | bin/add-track-json.pl data/trackList.json
JBrowse can also display VCF variation data directly from a VCF file on your web server that has been compressed with Heng Li’s bgzip and tabix. Simply place the .vcf.gz and .vcf.gz.tbi files in a directory accessible to your web server, and add a snippet of configuration to JBrowse to add the track, similar to:
{
"label" : "bam_variation",
"key" : "VCF simulated variation",
"storeClass" : "JBrowse/Store/SeqFeature/VCFTabix",
"urlTemplate" : "../../simulated-sorted.vcf.gz",
"type" : "HTMLVariants"
}
This can be added by either editing the data/trackList.json file with
a text editor, or by running something like this at the command line to
inject the track configuration:
echo ' {
"label" : "bam_variation",
"key" : "VCF simulated variation",
"storeClass" : "JBrowse/Store/SeqFeature/VCFTabix",
"urlTemplate" : "../../simulated-sorted.vcf.gz",
"type" : "HTMLVariants"
} ' | bin/add-track-json.pl data/trackList.json
JBrowse has a very powerful faceted track selector that can be used to search for tracks using metadata associated with them.
The track metadata is kept in a CSV-format file, with any number of columns, and with a “label” column whose contents must correspond to the track labels in the JBrowse configuration.
The demo bundle contains an example trackMetadata.csv file, which can
be copied into the data directory for use with this configuration.
cp trackMetadata.csv jbrowse/data
Then a simple faceted track selection configuration might look like:
trackSelector: {
type: 'Faceted',
},
trackMetadata: {
sources: [
{ type: 'csv', url: 'data/trackMetadata.csv' }
]
}
The jbrowse_conf.json file in the jbrowse directory already
conveniently contains this stanza, commented out. Uncomment it, refresh
your browser, and you should now see the faceted track selector
activated.
To highlight a region, you can either right-click on a feature and select ‘highlight this’, or you can set the highlight explicitly to a certain genomic region by clicking “View -> Set highlight” in the menu bar.
Beginning in JBrowse 1.10.0 you can also highlight a region with the mouse by clicking the highlighter tool (next to the Go button) and clicking and dragging to highlight a region.
JBrowse can display GFF3, BAM, BigWig, and VCF+Tabix files directly from your local machine without the need to transfer any data to the server. Just use the “File -> Open” tool from the menu bar to add tracks using local files.
Starting in version 1.10.0, users can define tracks that are combinations of the data in other tracks. The operations used to combine these tracks can be set operations (union, intersection, subtraction), arithmetic operations for quantitative tracks (addition, subtraction, multiplication, division), and/or masking operations to just highlight or mask some regions based on data in another track.
To add a combination track, select “File->Add combination track” from the menu bar, and drag existing tracks into the new combination track to start combining them.
If the old JBrowse is 1.3.0 or later, simply move the data directory from the old JBrowse directory into the new JBrowse directory.
See the accompanying slides (PDF)
Facts about “JBrowse Tutorial 2013”
| Has topic | JBrowse + |