dotplot#
- dotplot(data: AnnData, keys: Sequence[str] | Mapping[str, Sequence[str]], group_by: str, *, mapping: FeatureSpec | None = None, threshold: float = 0, size_scale: float = 1.0, variable_column: str = 'variable', color_low: str = '#e6e6e6', color_mid: str | None = None, color_high: str = '#D2042D', mid_point: Literal['mean', 'median', 'mid'] | float = 'mid', sort_by: str | Sequence[str] | None = None, sort_order: Literal['ascending', 'descending'] = 'descending', percentage_key: str = 'pct_exp', mean_key: str = 'avg_exp', rectangle: bool = True, dendrogram: bool = False, dendrogram_color: str = 'black', dendrogram_size: float = 0.5, dendrogram_kwargs: dict | None = None, rectangle_size: float = 0.8, rectangle_color: str = '#3f3f3f', rectangle_kwargs: dict | None = None, key_labels: bool = True, tooltips: Literal['none'] | Sequence[str] | FeatureSpec | None = None, interactive: bool = False, **geom_kwargs) PlotSpec#
Dotplot.
- Parameters:
data (
AnnData) – The AnnData object of the single cell data.keys (
Sequence[str] | Mapping[str,Sequence[str]]) – The variable keys to include in the dotplot. When a mapping is provided, each entry maps a group label to the keys belonging to that group; the keys are placed on the x-axis in mapping order. The same key cannot appear in more than one group.group_by (
str) – The key to group the data by.mapping (
FeatureSpec | None, defaultNone) – Aesthetic mappings for the plot, the result of aes().threshold (
float, default0) – The expression threshold to consider a gene as expressed.size_scale (
float, default1.0) – Scaling factor for the point sizes in the plot.point_size (
float, default1.0) – Scaling factor for the point sizes in the plot.variable_column (
str, default'variable') – Name for the variable column after unpivoting.color_low (
str, default'#e6e6e6') – Color for low values in the gradient.color_mid (
str | None, defaultNone) – Color for mid values in the gradient.color_high (
str, default'#D2042D') – Color for high values in the gradient.mid_point (
{'mean', 'median', 'mid'}| float, default'mid') – Midpoint for the color gradient.fill (
bool, optional) – Whether to use fill aesthetic instead of color, by default False.sort_by (
str | None) – The column to sort the results by, by default None.sort_order (
str, default'descending') – The sort order, either ‘ascending’ or ‘descending’.percentage_key (
str, default'pct_exp') – The name of the percentage column.mean_key (
str, default'avg_exp') – The name of the mean expression column.rectangle (
bool, defaultTrue) – Whether to add a rectangle border around the data areadendrogram (
bool, defaultFalse) – Whether to add a dendrogram for thegroup_byaxis. Usesscanpy.tl.dendrogramif not already computed. When True, group order is determined by the dendrogram.dendrogram_color (
str, default'black') – Color of the dendrogram segments.dendrogram_size (
float, default0.5) – Size (thickness) of the dendrogram segments.dendrogram_kwargs (
dict | None, defaultNone) – Additional parameters to pass to the dendrogram geom_segment.rectangle_size (
float, default0.8) – Size (thickness) of the rectangle border.rectangle_color (
str, default'#3f3f3f') – Color of the rectangle border.rectangle_kwargs (
dict | None, defaultNone) – Additional parameters to pass to the rectangle geom_rect.key_labels (
bool, defaultTrue) – Whether to draw bracket labels above the plot whenkeysis a mapping.tooltips (
{'none'}| Sequence[str] | FeatureSpec | None, defaultNone) – Tooltips to show when hovering over the geom. Accepts Sequence[str] or result of layer_tooltips() for more complex tooltips. Use ‘none’ to disable tooltips.show_tooltips (
bool, defaultTrue) – Whether to show tooltips.interactive (
bool, defaultFalse) – Whether to make the plot interactive.**geom_kwargs (
Any) – Additional keyword arguments for the geom_point layer.
- Returns:
PlotSpec– Dotplot.
Examples
A simple dotplot.
import scanpy as sc from lets_plot import * import cellestial as cl data = sc.read_h5ad("data/pbmc3k_pped.h5ad") markers = ["C1QA", "PSAP", "CD79A", "CD79B", "CST3", "LYZ"] dot = cl.dotplot( data, keys=markers, group_by="cell_type_lvl1", ) dot
Dotplot allows dendrograms among the groups.
dot = cl.dotplot( data, keys=markers, group_by="cell_type_lvl1", dendrogram=True, ) dot
Modify the dendrogram and rectangle borders.
dot = cl.dotplot( data, keys=markers, group_by="cell_type_lvl1", dendrogram=True, dendrogram_color="gray", dendrogram_size=1, rectangle_color="gray", rectangle_size=3, ) dot