thor.pl.deg

thor.pl.deg(data=None, genes=None, baseline_from_edge=[0, 0], cmaps=['Oranges', 'Blues'], lw=5, annotate=False, text_offset_x=0.08, text_offset_y=0, text_size=8, **subplots_kwds)[source]

Plot log2foldchange of gene expression against distance from the baseline.

Parameters:

  • data (pandas.DataFrame) – A DataFrame where rows represent windows/bins and columns include ‘distance’ and gene expression data.

  • genes (tuple or list of two list) – Lists of up-regulated and down-regulated genes to plot.

  • cmaps (tuple or list, optional) – Colormap names in matplotlib for plotting the genes. Default is [‘Oranges’, ‘Blues’].

  • lw (float, optional) – Line width for the plot. Default is 5.

  • annotate (bool, optional) – Whether to annotate the lines with the gene names. Default is False.

  • text_offset_x (float, optional) – Offset applied to the x position of the annotation texts. Default is 0.08.

  • text_offset_y (float, optional) – Offset applied to the y position of the annotation texts. Default is 0.

  • text_size (float, optional) – Size of the annotation texts. Default is 8.

  • **subplots_kwds (dict, optional) – Keyword arguments for the matplotlib.pyplot subplots function.

Notes

This function plots the log2foldchange of gene expression against the distance from the baseline for up-regulated and down-regulated genes separately.

Returns:

This function does not return any value. It generates the plot directly.

Return type:

None

Examples

>>> import pandas as pd
>>> import matplotlib.pyplot as plt

>>> # Assuming data is a pandas DataFrame with columns 'distance', 'gene1', 'gene2', etc.
>>> data = pd.DataFrame(...)
>>> up_genes = ['gene1', 'gene3', 'gene5']
>>> down_genes = ['gene2', 'gene4', 'gene6']
>>> genes = (up_genes, down_genes)

>>> # Plot the log2foldchange of gene expression against distance using default settings.
>>> fringe(data=data, genes=genes)

>>> # Plot the log2foldchange of gene expression against distance with custom settings.
>>> fringe(data=data, genes=genes, cmaps=['Reds', 'Greens'], lw=2, annotate=True, text_offset_x=0.1)