HoloNet.preprocessing.load_brca_visium_10x#
- HoloNet.preprocessing.load_brca_visium_10x()#
Load the example dataset
From the 10x Genomics website (https://www.10xgenomics.com/resources/datasets) From fresh frozen Invasive Ductal Carcinoma breast tissue (Block A Section 1) Profiled the expression of 24,923 genes in 3,798 spots
- Our preprocessing:
Exclude spots with less than 500 UMIs and genes expressed in less than 3 spots Normalize the expression matrix with the LogNormalize method in Seurat. Annotate the cell types by label transfer (the TransferData function in Seurat)
with single-cell breast cancer dataset GSE118390 as reference dataset.
Deconvolution results stored at adata.obsm[‘predicted_cell_type’] Cell-type label (the max value) stored at adata.obs.cell_type
- Return type
- Returns
: Annotated data matrix.