Cell Type Score Mode

Purpose

multiCelltypeScore uses the cell type annotation scores, such as the scores obtained from cell annotation deconvolution, to identify and characterize microenvironments with specific cell compositions and spatial distribution patterns within tissues.

Usage

SDAS cellularNeighborhood multiCelltypeScore -i st.h5ad --bin_size 100 -o outdir --score_key anno_score_cell2location \
--label_key anno_cell2location \
--cluster_method Kmeans

Input Parameter Description

Parameter	Required	Default	Description
-i / --input	Yes		Stereo-seq h5ad, containing cell type annotation results
-o / --output	Yes		Output folder
--bin_size	Yes		Bin size, used to control the size of points in the plot, not used for calculation, e.g., 20, 50, 100, cellbin (equivalent to 20)
--score_key	Yes		Column name in h5ad.obsm representing cell type score, must be a dataframe with header
--slice_key	No		Column name in h5ad.obs representing slice ID, used for window statistics and plotting in multi-slice analysis
--cluster_method	No	Kmeans	Clustering method, only Kmeans is available for singleCelltype mode; multi celltype score can choose leiden or Kmeans
--resolution	No	0.4	Resolution for leiden clustering when cluster_method is leiden; for bin20 or cellbin data, recommend resolution <0.1
--n_clusters	No	8	Number of clusters for Kmeans when cluster_method is Kmeans
--seed	No	42	Random seed
--label_key	No		Column name in h5ad.obs representing cell type annotation; if specified, neighborhood enrichment analysis for each CN will be performed

adata.obsm[score_key] file format example: header is cell type

Output Results Display

For detailed explanation and specific output results, please refer to the following link. (Single Cell Type Mode --> Output Results Display)

Parameter Tuning Suggestions

For detailed explanation, please refer to the following link. (Single Cell Type Mode --> Parameter Tuning Suggestions)