scSLAT.viz.multi_dataset.match_3D_celltype
- class scSLAT.viz.multi_dataset.match_3D_celltype(dataset_A, dataset_B, matching, highlight_celltype=[[], []], highlight_line='red', highlight_cell=None, meta=None, expr=None, subsample_size=300, reliability=None, scale_coordinate=False, rotate=None, exchange_xy=False, subset=None)[source]
Bases:
match_3D_multi
Highlight the celltype mapping, child of class:match_3D_multi()
- Parameters:
dataset_A (
pandas.core.frame.DataFrame
) – pandas dataframe which contain [‘index’,’x’,’y’]dataset_B (
pandas.core.frame.DataFrame
) – pandas dataframe which contain [‘index’,’x’,’y’]matching (
numpy.ndarray
) – matching resultshighlight_celltype (
typing.Optional
[typing.List
[typing.List
[str
]]]) – celltypes to highlight in two datasetshighlight_line (
typing.Union
[typing.List
[str
],str
,None
]) – color to highlight the linehighlight_cell (
typing.Optional
[str
]) – color to highlight the cellmeta (
typing.Optional
[str
]) – dataframe colname of meta, such as celltypeexpr (
typing.Optional
[str
]) – dataframe colname of gene exprsubsample_size (
typing.Optional
[int
]) – subsample size of matchesreliability (
typing.Optional
[numpy.ndarray
]) – if the match is reliablescale_coordinate (
typing.Optional
[bool
]) – if scale the coordinate via data - np.min(data)) / (np.max(data) - np.min(data))rotate (
typing.Optional
[typing.List
[str
]]) – how to rotate the slides (force scale_coordinate)change_xy – exchange x and y on dataset_B
subset (
typing.Union
[numpy.ndarray
,typing.List
[int
],None
]) – index of query cells to be plotted
Note
dataset_A and dataset_B can in different length
Methods
Draw lines between paired cells in two datasets