3k PBMCs from 10x Genomics.

The data consists in 3k PBMCs from a Healthy Donor and is freely available from 10x Genomics (here from this webpage).

The exact same data is also used in Seurat’s basic clustering tutorial.


This downloads 5.9 MB of data upon the first call of the function and stores it in ./data/pbmc3k_raw.h5ad.

The following code was run to produce the file.

adata = sc.read_10x_mtx(
'./data/filtered_gene_bc_matrices/hg19/',  # the directory with the `.mtx` file
var_names='gene_symbols',                  # use gene symbols for the variable names (variables-axis index)
cache=True)                                # write a cache file for faster subsequent reading

adata.var_names_make_unique()  # this is unnecessary if using 'gene_ids'
adata.write('write/pbmc3k_raw.h5ad', compression='gzip')
Return type



Annotated data matrix.