could you share the other 5 datasets detailed preprocessing codes about tosica

[JackieHanLab]

You can download the cell type annotation or reproduce the labels as follows:

For hArtery and hBone, you can reproduce the labels following the methods and cell type markers described in Liang, et.al, 2021 (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8685327/ , Fig. 2B and Table S1) and Chou, et.al, 2020 (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7331607/ , Table 1), respectively.

For mBrain, you can download from:
https://drive.google.com/drive/folders/1QQXDuUjKG8CTnwWW_u83MDtdrBXr8Kpq
We use the ‘cell_type’ as label.

For mAtlas, you can download from:
https://figshare.com/articles/dataset/Processed_files_to_use_with_scanpy_/8273102/2
We use the ‘cell_ontology_class’ as label.

For mPancreas:
https://ftp.ncbi.nlm.nih.gov/geo/series/GSE132nnn/GSE132188/suppl/GSE132188_adata.h5ad.h5
We use the sub-type from 'clusters_fig6_broad_final' and 'clusters_fig6_fine_final' as label.

And we use the Scanpy to normalize the counts data. The coda is shown as blow:
import scanpy as sc
sc.pp.normalize_total(adata, target_sum=1e4)
sc.pp.log1p(adata)
sc.pp.highly_variable_genes(adata)
adata = adata[:, adata.var.highly_variable]