splicejac.plot.signaling

functions to plot signaling strength and changes

Module Contents

Functions

plot_signaling_hubs(adata, cluster[, fontsize, ...])

Scatterplot of genes based on their signaling scores in a cell state

plot_signaling_change(adata, cluster1, cluster2[, ...])

Scatterplot of the gene signaling changes between two cell states

splicejac.plot.signaling.plot_signaling_hubs(adata, cluster, fontsize=10, top_genes=5, line_width=0.5, show_top_genes=True, criterium='weights', cmap='Reds', showfig=None, savefig=None, format='pdf', figsize=(3.5, 3))

Scatterplot of genes based on their signaling scores in a cell state

Parameters of matplotlib.pyplot.scatter are explained at: https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.scatter.html

adata: ~anndata.AnnData

count matrix

cluster: str

cell state

fontsize: int (default=10)

fontsize of figure

top_genes: int (default=5)

number of top genes to label with gene name

line_width: float (default=0.5)

line width for scatter plot

show_top_genes: Bool (default=True)

if True, annotate the top genes

criterium: str (default=’weights’)

criterium to rank top genes. “weights” ranks genes based on the weighted edges of the cell state GRN, “edges” ranks genes based on the number of edges

cmap: str (default: ‘Reds’)

the pyplot colormap for the scatter plot. A list of accepted color maps can be found at: https://matplotlib.org/stable/tutorials/colors/colormaps.html

showfig: Bool or None (default: None)

if True, show the figure

savefig: Bool or None (default: None)

if True, save the figure using the savefig path

format: str (default: ‘pdf’)

format of saved figure

figsize: tuple (default:(3.5,3))

size of figure

None

splicejac.plot.signaling.plot_signaling_change(adata, cluster1, cluster2, fontsize=10, top_genes=10, show_top_genes=True, criterium='weights', logscale_fc=True, x_shift=0.05, y_shift=0.05, cmap='coolwarm', line_width=0.5, showfig=None, savefig=None, format='pdf', figsize=(3.5, 3))

Scatterplot of the gene signaling changes between two cell states

adata: ~anndata.AnnData

count matrix

cluster1: str

first cell state

cluster2: str

second cell state

fontsize: int (default=10)

fontsize of figure

top_genes: int (default=10)

number of top genes to label with gene name

show_top_genes: Bool (default=True)

if True, annotate the top genes

criterium: str (default=’weights’)

criterium to rank top genes. “weights” ranks genes based on the weighted edges of the cell state GRN, “edges” ranks genes based on the number of edges

logscale_fc: Bool (default=True)

if True, rescale signaling change scores to logarithmic scale

x_shift: float (default: 0.05)

displacement on x-axis for gene annotations

y_shift: float (default: 0.05)

displacement on y-axis for gene annotations

cmap: str (default: ‘coolwarm’)

the pyplot colormap for the scatter plot. A list of accepted color maps can be found at: https://matplotlib.org/stable/tutorials/colors/colormaps.html

line_width: float (default=0.5)

line width for scatter plot

showfig: Bool or None (default: None)

if True, show the figure

savefig: Bool or None (default: None)

if True, save the figure using the savefig path

format: str (default: ‘pdf’)

format of saved figure

figsize: tuple (default:(3.5,3))

size of figure

None