# scviR The scviR package provides an experimental interface between R and [scvi-tools](https://docs.scvi-tools.org/en/stable/). Our first release addresses the use of the [totalVI model for CITE-seq data](https://docs.scvi-tools.org/en/stable/user_guide/models/totalvi.html). - The scviR vignette works through a chunk of the colab tutorial for [scvi-tools 0.19.0](https://colab.research.google.com/github/scverse/scvi-tutorials/blob/0.20.0/totalVI.ipynb); 0.20.0 employs muon, and this has not been addressed yet. - scviR defines python infrastructure via the [basilisk](https://bioconductor.org/packages/basilisk) discipline; the main python dependencies are declared in `R/basilisk.R`. - We have collected a number of intermediate results so that the outputs of totalVI (and other VI procedures) can be explored without taking the time to fit the model. An example in the CITE-seq domain is the anndata instance for the 5k-10k PBMC dataset with representations of the latent space, cluster assignments, and UMAP projection: ``` > tot = getTotalVI5k10kAdata() # retrieved on first call from Open Storage Network, cached > tot AnnData object with n_obs × n_vars = 10849 × 4000 obs: 'n_genes', 'percent_mito', 'n_counts', 'batch', '_scvi_labels', '_scvi_batch', 'leiden_totalVI' var: 'highly_variable', 'highly_variable_rank', 'means', 'variances', 'variances_norm', 'highly_variable_nbatches' uns: '_scvi_manager_uuid', '_scvi_uuid', 'hvg', 'leiden', 'log1p', 'neighbors', 'umap' obsm: 'X_totalVI', 'X_umap', 'denoised_protein', 'protein_expression', 'protein_foreground_prob' layers: 'counts', 'denoised_rna' obsp: 'connectivities', 'distances' > table(tot$obs$batch) PBMC5k PBMC10k 3994 6855 > dim(xx$obsm$get("X_totalVI")) # cell positions in 20 dimensional latent space [1] 10849 20 ``` Vignettes in the package show how to populate a Bioconductor SingleCellExperiment with components of this structure to help compare methods employed in the two frameworks.