mtopic.pl.feature_activity

mtopic.pl.feature_activity#

mtopic.pl.feature_activity(mdata, x, features, cmap='gnuplot', marker='.', s=10, p_top=99, fontsize=10, figsize=None, transparent=False, save=None)#

Visualize the distribution of specified features in a MuData object.

This function plots the spatial or embedding-based distribution of specified features (e.g., genes or proteins) across a sample dataset. Each feature is visualized individually, highlighting regions with high or low activity levels. This allows users to identify spatial patterns or clusters of cells associated with specific features.

Parameters:

  • mdata (muon.MuData) – A MuData object containing multimodal single-cell data, including spatial coordinates and expression matrices.

  • x (str) – The key in obsm of mdata representing the spatial coordinates or embeddings to use for plotting.

  • features (list) – A list of features (e.g., genes or proteins) to visualize.

  • cmap (str, optional) – The colormap to use for visualizing feature activity. Default is ‘gnuplot’.

  • marker (str, optional) – Marker style for scatter plots. Default is ‘.’.

  • s (int, optional) – Marker size in the scatter plots. Default is 10.

  • p_top (float, optional) – Percentile threshold to highlight top feature activity values. Points above this percentile are displayed prominently. Default is 99.

  • fontsize (int, optional) – Font size for plot titles and colorbar ticks. Default is 10.

  • figsize (tuple, optional) – Tuple specifying the figure size (width, height) in inches. If None, size is automatically determined based on the number of features. Default is None.

  • transparent (bool, optional) – If True, saves the figure with a transparent background. Default is False.

  • save (str, optional) – Path to save the figure. If None, the figure is displayed but not saved. Default is None.

Returns:

None

Example:
import mtopic

# Load MuData object
mdata = mtopic.read.h5mu("path/to/file.h5mu")

# Specify features to visualize
features = ['GeneA', 'GeneB', 'ProteinX']

# Plot spatial distribution of selected features
mtopic.pl.feature_activity(
    mdata,
    x='coords',
    features=features,
    cmap='viridis',
    save='feature_activity.png'
)