dash_bio_volcanoplot Examples and Reference

See VolcanoPlot in action.

VolcanoPlot

An example of a default VolcanoPlot component without any extra properties.

This example has not been ported to Julia yet - showing the Python version instead.

Visit the old docs site for Julia at: https://community.plotly.com/c/dash/julia/20

Effect sizes 

import pandas as pd
from dash import Dash, dcc, html, Input, Output, callback
import dash_bio as dashbio

app = Dash()

df = pd.read_csv('https://git.io/volcano_data1.csv')

app.layout = html.Div([
    'Effect sizes',
    dcc.RangeSlider(
        id='default-volcanoplot-input',
        min=-3,
        max=3,
        step=0.05,
        marks={i: {'label': str(i)} for i in range(-3, 3)},
        value=[-0.5, 1]
    ),
    html.Br(),
    html.Div(
        dcc.Graph(
            id='dashbio-default-volcanoplot',
            figure=dashbio.VolcanoPlot(
                dataframe=df
            )
        )
    )
])

@callback(
    Output('dashbio-default-volcanoplot', 'figure'),
    Input('default-volcanoplot-input', 'value')
)
def update_volcanoplot(effects):
    return dashbio.VolcanoPlot(
        dataframe=df,
        genomewideline_value=2.5,
        effect_size_line=effects
    )

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

Customization

Colors

Choose the colors of the scatter plot points, the highlighted points, the genome-wide line, and the effect size lines.

This example has not been ported to Julia yet - showing the Python version instead.

Visit the old docs site for Julia at: https://community.plotly.com/c/dash/julia/20

import pandas as pd
from dash import dcc
import dash_bio as dashbio

df = pd.read_csv('https://git.io/volcano_data1.csv')

volcanoplot = dashbio.VolcanoPlot(
    dataframe=df,
    effect_size_line_color='#AB63FA',
    genomewideline_color='#EF553B',
    highlight_color='#119DFF',
    col='#2A3F5F'
)

dcc.Graph(figure=volcanoplot)

Point Sizes And Line Widths

Change the size of the points on the scatter plot, and the widths of the effect lines and genome-wide line.

This example has not been ported to Julia yet - showing the Python version instead.

Visit the old docs site for Julia at: https://community.plotly.com/c/dash/julia/20

import pandas as pd
from dash import dcc
import dash_bio as dashbio

df = pd.read_csv('https://git.io/volcano_data1.csv')

volcanoplot = dashbio.VolcanoPlot(
    dataframe=df,
    point_size=10,
    effect_size_line_width=4,
    genomewideline_width=2
)

dcc.Graph(figure=volcanoplot)

dash_bio.VolcanoPlot is a Python-based component,
and may not be available in other languages.

Example Data