Intermediate tutorial: SCVI pipeline¶

Goal¶

Prepare data, run SCVI, and inspect downstream embeddings.

Inputs¶

AnnData object with count-like data and batch metadata.

Steps¶

import scanpy_plus as sp

adata_hvg = sp.pp.select_hvg(adata, batch_key="batch")
adata_hvg = sp.tl.clean_genes(adata_hvg)

model = sp.tl.run_scvi(adata_hvg)

# Visualize latent-space structure
sp.pl.plotly_umap(
    adata_hvg,
    color_col="leiden",
    obs_cols=["batch"],
    write_to_file="scvi_umap.html",
)

Expected output and interpretation¶

model is a fitted SCVI model for the selected features.
The output HTML UMAP allows interactive inspection of batch mixing and cluster structure.