Hello everyone! This release offers a couple important bug fixes.
For users of @jbrowse/react-linear-genome-view, we have fixes that improve
speed, CSS style consistency, and theming. We also have another speed
improvement for users with many scaffolds or contigs. Please see the release
notes below for more details!
Building on the plugin store on our website in the last release, we're now
excited to announce that plugins can be installed from within JBrowse Web!
Plugins from our plugin store can now be installed with the click of a button.
JBrowse Web now has the ability for tracks to use files on your local hard
drive. This is a great option if you want to visualize files you have locally
without uploading them to a server. These files will need to be re-opened each
time the app is opened or refreshed, but more robust handling of local files
will be available when we release JBrowse Desktop.
The MM and MP/ML tags can be used to color alignments tracks by either base
modifications or by methylation. The modifications mode is exciting because it
can show arbitrary DNA/RNA modifications, and the methylation mode uses
specific CpG context to show both modified and unmodified CpGs.
In this screenshot, the top alignments track is colored by methylation and the
bottom alignments track is colored by base modification.
One of the core aspects of JBrowse 2 is that it is an extensible
platform for biological visualization that can be extended with
plugins. We are excited to introduce the first version of our
plugin store, where we list the current external plugins that
are available. Check it out here.
In the coming weeks, we will also be bringing this plugin store directly
into the application, allowing plugin installation with the click of a button.
We're excited to introduce a new feature to JBrowse Web: built-in
SVG export of track visualizations! This feature currently supports
the linear genome view, and will be extended to more views in future
With the addition of this feature, it is now even easier to create
publication-ready screenshots of JBrowse views.
An important consideration for genomics software is scaling to very large
datasets. We have implemented a virtualization of our hierarchical track
selector, enabling it to support arbitrarily large track lists.
We're pleased to announce a new release of JBrowse Web!
To allow users to safely and seamlessly share advanced configurations in sessions, we now use Jexl to express configuration callbacks. Note that this is a breaking change, function()-style callbacks will no longer work.
Another new update is the first release of our interactive Storybook docs for the embeddable React Linear Genome View.
The docs contain live examples of how the LGV component can be used, along with source-code examples.
The site can be found here.
The alignments track received a couple updates including "large insertion indicators" for large indels, and also an upside-down count of clipping or insertion events. There is also a triangular indicator plotted when the insertion/clip count exceeds a threshold at that position defaulted to 30% of reads
Click and drag the overview bar to "Get sequence"#
Users can now download regions of sequence by selecting a region in the linear genome view and clicking "get sequence". See the demonstration video below:
You can also "get sequence" in the read vs reference view, which allows you to "get sequence" for the inserted bases or softclipped bases from a read alignment
We are excited to announce a new JBrowse 2 product:
JBrowseR builds on top of the
that we recently released.
Our React component inherits the general JBrowse 2 philosophy: it is
fully customizable and pluggable, like the core product.
The React component makes it very straightforward to embed a Linear
Genome View into a React app. However, this API can come with a steep
learning curve for bioinformaticians who may not be very familiar with
React. This is where JBrowseR comes in!
JBrowseR provides an R interface to the JBrowse 2 LGV React component.
Using JBrowseR, you can:
Embed the JBrowse 2 genome browser in R Markdown documents and Shiny applications
Deploy a genome browser directly from the R console to view your data
Customize your genome browser to display your own data
With this functionality, you can deploy a first-class genome browser with your data in just a few lines of R code!
For more information on getting started, check out the following resources: