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:

  • save_path (str (default: 'data/')) – Location to use when saving/loading the data.

  • protein_join (str (default: 'inner')) – Whether to take an inner join or outer join of proteins

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 during AnnData setup.

Return type:

AnnData

Examples

>>> import scvi
>>> adata = scvi.data.pbmcs_10x_cite_seq()