dash-bio

Dash Bio

Dash Bio is a suite of bioinformatics components built to work with Dash.

Announcement: https://medium.com/@plotlygraphs/announcing-dash-bio-ed8835d5da0c

Demo: https://dash-gallery.plotly.host/Portal/?search=Bioinformatics

Documentation: https://dash.plotly.com/dash-bio

Components

The Dash Bio components each fall into one of three categories:

• Custom chart types
• Sequence analysis tools
• 3D rendering tools

Custom chart types

• Dash Circos
• Dash Clustergram
• Dash Manhattan Plot
• Dash Needle Plot
• Dash Volcano Plot

Sequence analysis tools

• Dash Alignment Chart
• Dash Onco Print
• Dash Forna Container
• Dash Sequence Viewer

Visualization tools

• Dash Mol2D
• Dash Mol3D
• Dash Speck
• Dash Ngl

Using Dash Bio

It's easy to add a fully interactive chromosomal, molecular or genomic visualization to your Dash app by simply including the Dash Bio component into your app layout as follows:

import urllib.request as urlreq
from dash import Dash, html
import dash_bio as dashbio

app = Dash(__name__)

data = urlreq.urlopen(
    'https://raw.githubusercontent.com/plotly/dash-bio-docs-files/master/alignment_viewer_p53.fasta'
).read().decode('utf-8')

app.layout = html.Div([
    dashbio.AlignmentChart(
        id='my-default-alignment-viewer',
        data=data
    )
])

if __name__ == '__main__':
    app.run_server(debug=True)

See the Dash Bio documentation for more components and examples.

Run Dash Bio in a JupyterLab environment

• Create a virtual environment:

  The following steps require a virtual environment tool to be installed on your computer: pip install virtualenv

  a. On macOS and Linux: python3 -m venv env

  b. On Windows, enter: py -m venv env

• Activate your new environment:

  a. On macOS and Linux, enter: source env/bin/activate

  b. On Windows, enter: .\env\Scripts\activate

• Install required libraries (make sure you have pip installed with pip help):

pip install dash dash-bio pandas numpy Jupyterlab

• To run Dash inside Jupyter lab:

  a. Install jupyter-dash: pip install jupyter-dash

  b. Enter jupyter lab build

  (Note: This step requires Node.js and NPM installed on yourcomputer. To check if Node and NPM are installed, enter node -v and npm -v in your terminal. For install instructions see nodejs.org.

• To display Plotly figures in JupyterLab:

pip install jupyterlab "ipywidgets>=7.5”
jupyter labextension install jupyterlab-plotly@4.14.3

• Start JupyterLab by typing: jupyter lab

  Important: JupyterLab must be run within the virtual environment that was previously activated.

For more on running a Dash app in Jupyter Lab visit Getting Started with Jupyter Dash.

Dash

Learn more about Dash at https://plotly.com/products/dash/.

Consulting and OEM

For inquiries about Dash app development, advanced OEM integration, and more, please reach out.

Contributing and Local Development

If you would like to contribute to this repository, or run demo apps and tests, please refer to the contributing guidelines.

Changelog

[1.0.2] - 2022-03-18

Fixed

• #675 Fixed an issue with the JS resource files in the npm release of dash-bio. As pointed out in this community post some of the dependencies have not been resolved at their external unpkg URL.
• #671 Fixed Onco-Print range property description.