BrainSmallDataset¶

class scvi.dataset.BrainSmallDataset(save_path='data/', save_path_10X='data/', delayed_populating=False, remove_extracted_data=False)[source]¶

Bases: scvi.dataset.dataset10X.Dataset10X

This dataset consists in 9,128 mouse brain cells profiled using 10x Genomics.

It is used as a complement of PBMC for our study of zero abundance and quality control metrics correlation with our generative posterior parameters.

We derived quality control metrics using the cellrangerRkit R package (v.1.1.0). Quality metrics were extracted from CellRanger throughout the molecule specific information file. We kept the top 3000 genes by variance. We used the clusters provided by cellRanger for the correlation analysis of zero probabilities.

Examples

>>> gene_dataset = BrainSmallDataset()