mcmicro_to_scimap
Short Description
sm.pp.mcmicro_to_scimap
: The function allows users to directly import the output from mcmicro
into scimap
.
Function
mcmicro_to_scimap(feature_table_path, remove_dna=True, remove_string_from_name=None, log=True, drop_markers=None, random_sample=None, unique_CellId=True, CellId='CellID', split='X_centroid', custom_imageid=None, min_cells=None, output_dir=None)
Parameters:
Name | Type | Description | Default |
---|---|---|---|
feature_table_path |
list
|
This is a list of paths that lead to the single-cell spatial feature tables. Each image should have a unique path assigned to it. |
required |
remove_dna |
bool
|
Remove the DNA channels from the final output. Looks for channels with the string 'dna' in it. |
True
|
remove_string_from_name |
string
|
Used to clean channel names. The given string will be removed from all marker names. |
None
|
log |
bool
|
Take Log of data (log1p transformation will be applied). |
True
|
drop_markers |
list
|
List of markers to drop from the analysis. e.g. ["CD3D", "CD20"]. |
None
|
random_sample |
int
|
Randomly sub-sample data, new sample contains desired number of cells. |
None
|
CellId |
string
|
Name of the column that contains the cell ID. |
'CellID'
|
unique_CellId |
bool
|
By default, the function creates a unique name for each cell/row by combining the
|
True
|
split |
string
|
To split the CSV into counts table and meta data, pass in the name of the column that immediately follows the marker quantification. |
'X_centroid'
|
custom_imageid |
string
|
Pass a user defined Image ID. By default the name of the CSV file is used. |
None
|
min_cells |
int
|
Images with less cells than int will be dropped Particulary useful when importing multiple images. |
None
|
output_dir |
string
|
Path to output directory. |
None
|
Returns:
Type | Description |
---|---|
AnnData Object |
1 2 3 |
|
Source code in scimap/preprocessing/_mcmicro_to_scimap.py
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