dash-bio
v1.0.2
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Dash components for bioinformatics
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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
andnpm -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 [email protected]
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.