insitupy.plotting.volcano_plot

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insitupy.plotting.volcano_plot#

insitupy.plotting.volcano_plot(data, logfoldchanges_column='logfoldchanges', pval_column='neg_log10_pvals', significance_threshold=0.05, fold_change_threshold=1, title=None, adjust_labels=True, ax=None, savepath=None, save_only=False, dpi_save=300, show=True, label_top_n=20, figsize=(8, 6), config_table=None)#

Create a volcano plot from the DataFrame and label the top 20 most significant up and down-regulated genes. For the generation of the input data insitupy.utils.deg.create_deg_dataframe can be used

Parameters:

  • data (pd.DataFrame) – DataFrame containing gene names, log fold changes, and p-values.

  • logfoldchanges_column (str) – Column name for log fold changes (default is ‘logfoldchanges’).

  • pval_column (str) – Column name for negative log10 p-values (default is ‘neg_log10_pvals’).

  • significance_threshold (float) – P-value threshold for significance (default is 0.05).

  • fold_change_threshold (float) – Log2 fold change threshold for up/down regulation (default is 1).

  • title (str) – Title of the plot (default is “Volcano Plot”).

  • adjust_labels (bool, optional) – If True, adjusts the labels to avoid overlap. Default is False.

  • savepath (Union[str, os.PathLike, Path], optional) – Path to save the plot (default is None).

  • save_only (bool) – If True, only save the plot without displaying it (default is False).

  • dpi_save (int) – Dots per inch (DPI) for saving the plot (default is 300).

  • label_top_n (int) – Number of top up- and downregulated genes to label in the plot (default is 20).

  • figsize (Tuple[int, int]) – Size of the figure in inches (default is (8, 6)).

Returns:

None

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