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Volcano Plot interactively identifies clinically meaningful markers in genomic experiments, i.e., markers that are statistically significant and have an effect size greater than some threshold. Specifically, volcano plots depict the negative log-base-10 p-values plotted against their effect size.
importpandasaspdimportdash_biodf=pd.read_csv('https://raw.githubusercontent.com/plotly/dash-bio-docs-files/master/volcano_data1.csv') dash_bio.VolcanoPlot( dataframe=df, )
Change the size of the points on the scatter plot, and the widths of the effect lines and genome-wide line.
importpandasaspdimportdash_biodf=pd.read_csv('https://raw.githubusercontent.com/plotly/dash-bio-docs-files/master/volcano_data1.csv') dash_bio.VolcanoPlot( dataframe=df, point_size=10, effect_size_line_width=4, genomewideline_width=2 )
fromIPython.displayimportIFramesnippet_url='https://python-docs-dash-snippets.herokuapp.com/python-docs-dash-snippets/'IFrame(snippet_url+'bio-volcano', width='100%', height=1200)