Multimodal

• CITE-seq analysis with totalVI
• Reference mapping with SCVI-Tools
• CITE-seq reference mapping with totalVI
• Integration of CITE-seq and scRNA-seq data
• Joint analysis of paired and unpaired multiomic data with MultiVI
• Semi-supervised CITE-seq analysis with TotalANVI
• Comparing integration metrics using scib-metrics package
• Plotting confusion matrices
• Visualizing the embeddings and denoised protein values
• Integration of scRNA-seq and spatial proteomics data with DiagVI
• Integration of scRNA-seq and spatial transcriptomics data with DiagVI

CITE-seq analysis with totalVI

Go through the totalVI workflow to analyze CITE-seq datasets

Multimodal

Reference mapping with SCVI-Tools

Map cells from a query dataset to the latent space of a reference dataset with the scArches method

Multimodal

CITE-seq reference mapping with totalVI

Use totalVI to train a reference model and map CITE-seq query data

Multimodal

Integration of CITE-seq and scRNA-seq data

Use totalVI to integrate CITE-seq and scRNA-seq datasets

Multimodal

Joint analysis of paired and unpaired multiomic data with MultiVI

Go through the MultiVI workflow to perform joint analysis of paired and unpaired multi omic data

Multimodal

Comparing integration metrics using scib-metrics package

Use TotalANVI to perform semi-supervised analysis of CITE-seq data, leveraging partial cell type annotations for label prediction, protein imputation, and differential abundance

Multimodal

Integration of scRNA-seq and spatial proteomics data with DiagVI

Perform integration of spatial proteomics and single-cell transcriptomics data with DiagVI

Multimodal

Integration of scRNA-seq and spatial transcriptomics data with DiagVI

Perform integration of spatial and single-cell transcriptomics data with DiagVI

Multimodal