User guide

Navigating the UI

Linear genome view usage

To start a linear genome view, use the menu bar

File->Add->Linear genome view

Using the location search box

  • Use the search box in the LGV
  • Enter syntax chr1:1-100 or chr1:1..100
  • You can also specify an assembly name with the locstring {hg19}chr1:1-100

Note: searching by gene name is not yet available but will be added soon!


Mouse wheel can scroll side to side, as well as click and drag. The pan buttons also exist in the header of the linear genome view


The zoom buttons exist in the header of the linear genome view, and there is also a slider bar to zoom in and out.

Note: You can also hold the "Ctrl" key and use your mousewheel or trackpad to scroll and this will zoom in and out

Re-ordering tracks

There is a drag handle on the track labels indicating by the six dots, clicking and dragging on this part of the track label can reorder tracks

Adding tracks

To add a new track or connection, you can use the menu bar in the app to open the form for adding a track:

File->Open Track

The \"Add track form\"

Note: There is also a circular "+" button inside the track selector menu that can also be used to access the "Add track" form.

The \"Add track button\" in the tracklist

In the "Add track" form, you can provide a URL to a file to load. Opening files from your local machine is not supported currently in the jbrowse-web app (jbrowse-desktop does allow this though, and may be added to jbrowse-web in the future)

Paste a URL to a file and optionally provide an index file URL too. The following file formats are supported

  • Tabixed VCF
  • Tabixed BED
  • Tabixed GFF
  • BAM
  • CRAM
  • BigWig
  • BigBed
  • .hic file (Juicebox)

For tabix files, TBI or CSI indexes are allowed. CSI or BAI is allowed for BAM. Only CRAI is allowed for CRAM. The index will be inferred for BAI or TBI files as filename+'.bai' for example, but if it is different than this, make sure to specify the index file explicitly.

Note: If you are an administrator, you can add tracks with the command line or with the admin server add-track or admin-server guide

Sharing sessions

The main menu bar has a "Share" button to enable users to share their sessions with other people. The share button generates a URL that can be sent to other users. It is not possible to copy your URL bar and send this to another user currently, because sessions can become too large for the address bar in many cases.

Note that you can copy and paste URLs between different tabs in your local browser though

The session URL will contain

  • what views are on the screen, and settings for the views (e.g. track labels overlapping or offset)
  • what tracks are in the view
  • extra tracks that you added with the "Add track workflow"
  • for the alignments track, the show soft clipping and sort settings on the pileup
  • etc

All this stuff gets included in the session

This means you can share links with your custom tracks with other users, without being a JBrowse admin!

Editing track configs

Currently, in order to edit a track config, you have to make a copy of the track

Figure showing how to copy a track, note that settings button is disabled because we don't \"own this track\" as a non-privileged user

After you have copied the track, you can edit the track settings

Figure showing the settings button is now enabled on the session track, and you have full control over your session tracks

Your new track is a so-called "session track" and can be shared with other users with the "Share" button

Rubberband selection

The scale bars accept a click and drag action to select a region

Rubberband selection can be performed on both the region and overview scale bars

Track label positioning

Track labels can be positioned on their own row or overlapping the data to save vertical screen space. They can also be hidden. This is done by clicking on the hamburger menu for a specific view.

Example of using the overlap and offset track label positioning options

Horizontally flip

The view can be horizontally flipped, or reverse complemented, to make the coordinates go from right to left instead of left to right

We use triangles pointing in the direction of the orientation in the overview bar to help indicate whether the app is horizontally flipped or not

Here is an example of before and after horizontally flipping the view

Before and after horizontally flipping

Alignments tracks

Visualizing alignments is an important aspect of genome browsers. This guide will go over the main features of the "Alignments track"

The alignments track is a combination of a pileup and a coverage visualization

Pileup visualization

The pileup is the lower part of the alignments track and shows each of the reads as boxes positioned on the genome.

By default the reads are colored red if they aligned to the forward strand of the reference genome, or blue if they aligned to the reverse strand.

Coverage visualization

The coverage visualization shows the depth-of-coverage of the reads at each position on the genome, and also draws using colored boxes any occurrence of mismatches between the read and the reference genome, so if 50% of the reads had a T instead of the reference A, half the height of the coverage histogram would contain a 'red' box

Screenshot showing the alignments track, which contains both a coverage view at the top and a pileup view at the bottom

Show soft clipping

If a read contains bases that do not map the the genome properly, they can either be removed from the alignment (hard clipping) or can be included, and not shown by default (soft clipping)

JBrowse 2 also contains an option to "show the soft clipping" that has occurred. This can be valuable to show the signal around a region that contains structural variation or difficult mappability

Shows what turning on soft-clipping enables for a simulated long-read dataset. There is a simulated structural variant, a deletion, at this position, so the read has bases that map to the other side of the deletion being revealed by this.

Sort by options

The alignments tracks can also be configured to "sort by" a specific attribute for reads that span the center line.

By default the center line is not shown, but by showing it (Go to the view's hamburger menu->Select "Show center line") then you will obtain a better idea of what the "sort by" option is doing

Showing the center line

Here is how to turn on the center line

  1. Open the hamburger menu in the top left of the linear genome view
  2. Select "Show center line"

Illustrates before and after turning on the center line. The center line is an indicator that shows what base pair underlies the center of the view. Note that this is used in the \"Sort by\" option discussed below; the sort is performed using properties of the feature or even exact base pair underlying the center line

Sorting by base

Sorting by base will re-arrange the pileup so that the reads that have a specific base-pair mutation at the position crossing the center line (which is 1bp wide) will be arranged in a sorted manner. To enable Sort by base

  1. Open the track menu for the specific track using the vertical '...' in the track label
  2. Select 'Sort by'->'Base pair'

Illustrating the pileup re-ordering that happens when turning on the Sort by->Base pair. The sorting is done by specifically what letter of each read underlies the current center line position (the center line is 1bp wide, so sorted by that exact letter)

There are other sorting options available and more to come. If you have any requests please drop us a line via github here

BigWig tracks

Visualizing genome signals, whether it is read depth-of-coverage or other signal, can often be done by using BigWig files

This figure shows a BigWig using the XY plot renderer

Line plot version of a BigWig

There are many options for controlling the BigWig which can be accessed from the UI. See the bigwig configuration guide

Linear synteny and dotplot views

The dotplot view is a 2D comparative view that can display alignments between different genome assemblies, or even compare a long-read or NGS short-read versus the genome

Opening a dotplot view

Currently the workflow for launching a dotplot is done by navigating in the header bar to the File->Add->Dotplot view

This will let you select the genome assemblies of interest

Then you can also provide a synteny file in the form of PAF via the Add track workflow

Then currently you must configuration edit the PAFAdapter to indicate the two assemblies in the PAFAdapter

Adding a new dotplot or synteny view via the menubar

Example of the import form for a dotplot or synteny view. Allows you to select two different assemblies and a PAF file can be supplied via a URL

Example of a dotplot visualization of the grape vs the peach genome

See the dotplot configuration for more detailed descriptions

Opening a linear synteny view

Use the main menu bar to select

File->Add->Linear synteny view

Adding a new linear-synteny-view via the menubar

Example of the import form for a synteny view allowing you to select two different assemblies and optionally adding a PAF file via a URL

Figure showing grape vs peach synteny

See the linear synteny configuration for more details on manually configuring the synteny view

Long read vs reference plots

One can also launch a dotplot view that compares a long read to the reference genome by

  • Right clicking an alignment
  • Select "Dotplot read vs ref" or "Linear read vs ref" in the context menu

Example of a dotplot of a long read vs the reference genome

Example of a \"synteny\" view of a long read vs the reference genome

Hi-C tracks

Visualizing Hi-C data can be performed with .hic files which are generated by the Juicebox software suite. It uses the hic-straw module developed by the juicebox/igv.js team to visualize it in jbrowse.

Currently configuration options are basic for Hi-C tracks, see configuration for info about configuring Hi-C


Screenshot showing a Hi-C track

SV inspector

The SV inspector is a "workflow" that is designed to help users inspect structural variant calls

Opening the SV inspector

We can start the SV inspector by launching it from the App level menu bar

The SV inspector can be launched from the main menu bar

This will bring up an "import form" that asks you for your SV evidence. This can be provided using a URL in these formats:

  • VCF (plain text VCF, not tabix VCF)
  • STAR-fusion result file
  • or other formats

SV inspector import form

Example SV inspector workflow

We can start the SV inspector workflow by opening up this file containing translocation events called from a breast cancer cell line SKBR3, based on these published data

## Example VCF for use in the SV inspector

Copy this URL and paste it into the import form and select hg19

SV inspector import form with URL

SV inspector results

After loading the user's requested file, you will have a spreadsheet with each row representing a row of the file you opened, along with a whole-genome overview of the SVs on the right

SV inspector with loaded results

Now here is where things can become interesting

We can perform searching and filtering on the table, which can filter down the number of rows being displayed, and then this dynamically filters the circos view on the right also.

SV inspector with filter applied

Launching breakpoint split view

By clicking on the features in the Circos, or clicking on the triangle drop-down on the leftmost column of the spreadsheet, we can dynamically launch a new view of the data that is called the "split view" or the "breakpoint split view"

This allows us to inspect the breakpoints of the structural variant, and compare each side to the alignments.

Variant tracks

Visualizing variant tracks from the VCF format alongside the original alignment evidence track is a common workflow for validating your results. In JBrowse 2 we can open a variant track and an alignments track as shown below

Variant track indicating a SNP alongside the alignment track evidence

Variant widget

The variant features have a specialized widget that contains a table indicating all the calls that were made in a multi-sample VCF. Some VCF files, like the 1000 genomes VCF, can contain thousands of samples in a single file. This table can display the details

Future additions

We anticipate adding more features to the variant track in the future including

  1. Ability to visualize individual samples in a multi-sample VCF as subtracks of a variant track
  2. Ability to use FILTER the VCF column via the track menu