scanpy.pl.pca_overview

scanpy.pl.pca_overview(adata, **params)

Plot PCA results.

The parameters are the ones of the scatter plot. Call pca_ranking separately if you want to change the default settings.

Parameters:

adata AnnData

Annotated data matrix.

color

Keys for observation/cell annotation either as list ["ann1", "ann2"] or string "ann1,ann2,...".

use_raw

Use raw attribute of adata if present.

sort_order

For continuous annotations used as color parameter, plot data points with higher values on top of others.

groups

Restrict to a few categories in categorical observation annotation. The default is not to restrict to any groups.

dimensions

0-indexed dimensions of the embedding to plot as integers. E.g. [(0, 1), (1, 2)]. Unlike components, this argument is used in the same way as colors, e.g. is used to specify a single plot at a time. Will eventually replace the components argument.

components

For instance, ['1,2', '2,3']. To plot all available components use components='all'.

projection

Projection of plot (default: '2d').

legend_loc

Location of legend, either 'on data', 'right margin' or a valid keyword for the loc parameter of Legend.

legend_fontsize

Numeric size in pt or string describing the size. See set_fontsize().

legend_fontweight

Legend font weight. A numeric value in range 0-1000 or a string. Defaults to 'bold' if legend_loc == 'on data', otherwise to 'normal'. See set_fontweight().

legend_fontoutline

Line width of the legend font outline in pt. Draws a white outline using the path effect withStroke.

colorbar_loc

Where to place the colorbar for continous variables. If None, no colorbar is added.

size

Point size. If None, is automatically computed as 120000 / n_cells. Can be a sequence containing the size for each cell. The order should be the same as in adata.obs.

color_map

Color map to use for continous variables. Can be a name or a Colormap instance (e.g. "magma”, "viridis" or mpl.cm.cividis), see get_cmap(). If None, the value of mpl.rcParams["image.cmap"] is used. The default color_map can be set using set_figure_params().

palette

Colors to use for plotting categorical annotation groups. The palette can be a valid ListedColormap name ('Set2', 'tab20', …), a Cycler object, a dict mapping categories to colors, or a sequence of colors. Colors must be valid to matplotlib. (see is_color_like()). If None, mpl.rcParams["axes.prop_cycle"] is used unless the categorical variable already has colors stored in adata.uns["{var}_colors"]. If provided, values of adata.uns["{var}_colors"] will be set.

na_color

Color to use for null or masked values. Can be anything matplotlib accepts as a color. Used for all points if color=None.

na_in_legend

If there are missing values, whether they get an entry in the legend. Currently only implemented for categorical legends.

frameon

Draw a frame around the scatter plot. Defaults to value set in set_figure_params(), defaults to True.

title

Provide title for panels either as string or list of strings, e.g. ['title1', 'title2', ...].

vmin

The value representing the lower limit of the color scale. Values smaller than vmin are plotted with the same color as vmin. vmin can be a number, a string, a function or None. If vmin is a string and has the format pN, this is interpreted as a vmin=percentile(N). For example vmin=’p1.5’ is interpreted as the 1.5 percentile. If vmin is function, then vmin is interpreted as the return value of the function over the list of values to plot. For example to set vmin tp the mean of the values to plot, def my_vmin(values): return np.mean(values) and then set vmin=my_vmin. If vmin is None (default) an automatic minimum value is used as defined by matplotlib scatter function. When making multiple plots, vmin can be a list of values, one for each plot. For example vmin=[0.1, 'p1', None, my_vmin]

vmax

The value representing the upper limit of the color scale. The format is the same as for vmin.

vcenter

The value representing the center of the color scale. Useful for diverging colormaps. The format is the same as for vmin. Example: sc.pl.umap(adata, color=’TREM2’, vcenter=’p50’, cmap=’RdBu_r’)

add_outline

If set to True, this will add a thin border around groups of dots. In some situations this can enhance the aesthetics of the resulting image

outline_color

Tuple with two valid color names used to adjust the add_outline. The first color is the border color (default: black), while the second color is a gap color between the border color and the scatter dot (default: white).

outline_width

Tuple with two width numbers used to adjust the outline. The first value is the width of the border color as a fraction of the scatter dot size (default: 0.3). The second value is width of the gap color (default: 0.05).

ncols

Number of panels per row.

wspace

Adjust the width of the space between multiple panels.

hspace

Adjust the height of the space between multiple panels.

return_fig

Return the matplotlib figure.

kwargs

Arguments to pass to matplotlib.pyplot.scatter(), for instance: the maximum and minimum values (e.g. vmin=-2, vmax=5).

show

Show the plot, do not return axis.

save

If True or a str, save the figure. A string is appended to the default filename. Infer the filetype if ending on {'.pdf', '.png', '.svg'}.

Examples

import scanpy as sc
adata = sc.datasets.pbmc3k_processed()
sc.pl.pca_overview(adata, color="louvain")

See also

pp.pca