如何用距离滑翔机改变火山图的genomewideline_value

Question

我正试图绘制一个火山图，并且我想根据Range Slider值来更改genomewideline_value，但是它不起作用。下面是我的示例代码：

import pandas as pd
import dash
from dash.dependencies import Input, Output
import dash_bio as dashbio
from dash import html, dcc

app = dash.Dash(__name__)
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]
    ),
    dcc.RangeSlider(
        id='default-volcanoplot-input-2',
        min=-3,
        max=3,
        step=0.05,
        marks={j: {'label': str(j)} for j in range(-3, 3)},
        value=[0.5]
    ),    
    html.Br(),
    html.Div(
        dcc.Graph(
            id='dashbio-default-volcanoplot',
            figure={}
            )
        )
])

@app.callback(
    Output('dashbio-default-volcanoplot', 'figure'),
    [Input('default-volcanoplot-input', 'value'),
    Input('default-volcanoplot-input-2', 'value')]
)
def update_volcanoplot(effects,effects_2):
    return dashbio.VolcanoPlot(
        dataframe=df,
        effect_size='EFFECTSIZE', 
        logp=True,
        p='P', 
        snp=None,
        gene='GENE',
        genomewideline_value=effects_2,
        genomewideline_width = 1,
        effect_size_line=effects,
        effect_size_line_width = 1,
        xlabel='log2 Fold Change', 
        ylabel='-(p-adjusted)')

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

在运行此代码时，出现了如下错误：ValueError: ('Lengths must match to compare', (9934,), (1,))

如果我将genomewideline_value=effects_2更改为genomewideline_value=0.5，它工作得很好，但我不能通过滑块改变它。

在这种情况下我该怎么办。谢谢。

Answer 1

我不使用偶发或Dash，但我想我在运行代码时注意到的是，genomewideline_value只接受单个值，而不是接受范围值。如果我将它从一个范围滑块更改为一个下拉滑块，则更改是按照预期进行的。我已经在Colab环境中测试过jupyter_dash模块，所以请为您的环境修改它。

import pandas as pd
import dash
from dash.dependencies import Input, Output
import dash_bio as dashbio
from dash import html, dcc

#app = dash.Dash(__name__)
app = JupyterDash(__name__)

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

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]
    ),
    dcc.Dropdown(id='volcanpplot_dp',
                 options=[0,1,2,3,4,5,6,7,8],
                 value=4        
    ),
    html.Br(),
    html.Div(
        dcc.Graph(
            id='dashbio-default-volcanoplot',
            figure=dashbio.VolcanoPlot(
                dataframe=df
            )
        )
    )
])

@app.callback(
    Output('dashbio-default-volcanoplot', 'figure'),
    [
     Input('default-volcanoplot-input', 'value'),
     Input('volcanpplot_dp', 'value')
     ]
)
def update_volcanoplot(effects, effects2):
    return dashbio.VolcanoPlot(
        dataframe=df,
        point_size=8,
        genomewideline_value=effects2,
        genomewideline_width=2,
        effect_size_line=effects,
        effect_size_line_width=2,
    )

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

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