From cell-type stratified features to multicellular coordinated programs
This document provides a comprehensive reference for the MuVIcell package API.
load_muon_data(path)- Load muon data from filesave_muon_data(mdata, path)- Save muon data to file
normalize_views(mdata, ...)- Normalize data in each viewfilter_views(mdata, ...)- Filter cells and genesfind_highly_variable_genes(mdata, ...)- Find HVGssubset_to_hvg(mdata, ...)- Subset to HVGspreprocess_for_muvi(mdata, ...)- Complete preprocessing pipeline
muvi_reconstruction_info(model, mdata, ...)- Assess reconstruction performancemuvi_variance_by_view_info(model, ...)- Analyze variance explainedmuvi_featureclass_variance_info(model, mdata, ...)- Variance by feature classmuvi_variable_loadings_info(model, mdata, ...)- Extract variable loadmuvi_selected_features_info(variable_loadings, ...)- Get feature loadingsmuvi_factor_scores_info(model, mdata, ...)- Get factor scores with metadatamuvi_kruskal_info(scores_df, ...)- Kruskal-Wallis test for categorical variablesmuvi_kendall_info(scores_df, ...)- Kendall's tau for ordinal variablesmuvi_confidence_ellipses_info(scores_df, ...)- Confidence for factor pairsmuvi_top_features_by_view_info(variable_loadings, ...)- Top features by viewmuvi_top_features_by_class_info(variable_loadings, ...)- Top features by classmuvi_build_selected_anndata(mdata, selection_df, ...)- Export to AnnData
muvi_reconstruction_plot(stats_df, ...)- Plot reconstruction performancemuvi_variance_by_view_plot(df, ...)- Plot variance explained by viewmuvi_featureclass_variance_plot(df, ...)- Plot variance by feature classmuvi_plot_top_loadings_heatmap(variable_loadings, ...)- Heatmap of top loadingsmuvi_selected_features_plot(df_long, ...)- Plot selected feature loadingsmuvi_violin_plot(scores_df, ...)- Violin plots of factor scoresmuvi_confidence_ellipses_plot(scores_df, ellipses_df, ...)- Plot confidence
generate_synthetic_data(...)- Generate synthetic multi-view dataadd_latent_structure(mdata, ...)- Add latent factor structuregenerate_batch_effects(mdata, ...)- Add batch effectssimulate_missing_data(mdata, ...)- Simulate missing data
For detailed parameter descriptions and examples, see the function docstrings and tutorial notebook.