scvi.data.pbmcs_10x_cite_seq#
- scvi.data.pbmcs_10x_cite_seq(save_path='data/', protein_join='inner')[source]#
Filtered PBMCs from 10x Genomics profiled with RNA and protein.
Datasets were filtered for doublets and other outliers as in https://github.com/YosefLab/totalVI_reproducibility/blob/master/data/data_filtering_scripts/pbmc_10k/pbmc_10k.py
- Parameters:
- Return type:
- Returns:
AnnData with batch info (
.obs['batch']
), and protein expression (.obsm["protein_expression"]
)Missing protein values are zero, when
protein_join == "outer
and are identified duringAnnData
setup.
Examples
>>> import scvi >>> adata = scvi.data.pbmcs_10x_cite_seq()