APIΒΆ
Metacells single-cell RNA sequencing.
- Pipeline
- Related Genes
relate_to_lateral_genes()- Exclude
exclude_genes()exclude_cells()extract_clean_data()- Mark (Genes)
mark_lateral_genes()mark_noisy_genes()mark_select_genes()mark_ignored_genes()mark_essential_genes()- Selection
extract_selected_data()- Direct
compute_direct_metacells()- Divide and Conquer
set_max_parallel_piles()get_max_parallel_piles()guess_max_parallel_piles()compute_target_pile_size()divide_and_conquer_pipeline()compute_divide_and_conquer_metacells()- Collect
collect_metacells()- UMAP
compute_knn_by_markers()compute_umap_by_markers()- Projection
projection_pipeline()outliers_projection_pipeline()write_projection_weights()- MCView
compute_for_mcview()
- Tools
- General Tools
- Filtering the Data
- Filter
filter_data()- Mask
combine_masks()- Properly Sampled
compute_excluded_gene_umis()find_properly_sampled_cells()find_properly_sampled_genes()- Named
find_named_genes()- High
find_high_total_genes()find_high_topN_genes()find_high_fraction_genes()find_high_normalized_variance_genes()find_high_relative_variance_genes()find_metacells_marker_genes()- Noisy Lonely
find_bursty_lonely_genes()- Rare
find_rare_gene_modules()
- Building the Graph
- Computing the Metacells
- Evaluating the Metacells
- Group
group_obs_data()group_obs_annotation()- Quality
compute_stdev_logs()compute_projected_folds()compute_similar_query_metacells()compute_outliers_matches()compute_deviant_folds()compute_inner_folds()compute_type_genes_normalized_variances()compute_outliers_fold_factors()count_significant_inner_folds()compute_distinct_folds()find_distinct_genes()compute_subset_distinct_genes()
- Visualizing the Metacells
- Projecting onto Metacells
- Parameters
- Defaults
significant_gene_fractionsignificant_gene_normalized_variancesignificant_gene_relative_variancesignificant_gene_similaritysignificant_gene_fold_factorsignificant_noisy_gene_fold_factorsignificant_valuedownsample_min_samplesdownsample_min_cell_quantiledownsample_max_cell_quantilerelative_variance_window_sizesimilarity_methodlogistics_locationlogistics_slopemin_target_pile_sizemax_target_pile_sizetarget_metacells_in_piletarget_metacell_sizetarget_metacell_umismetacell_geo_meanmetacell_umis_regularizationzeros_cell_size_quantilecell_umismin_split_size_factormin_robust_size_factormax_merge_size_factormin_metacell_sizemax_split_min_cut_strengthmin_cut_seed_cellspiles_min_split_size_factorpiles_min_robust_size_factorpiles_max_merge_size_factorproperly_sampled_min_cell_totalproperly_sampled_max_cell_totalproperly_sampled_min_gene_totalproperly_sampled_max_excluded_genes_fractionrelated_max_sampled_cellsrelated_genes_similarity_methodrelated_genes_cluster_methodrelated_max_genes_of_modulesrelated_min_mean_gene_fractionrelated_min_gene_correlationbursty_lonely_max_sampled_cellsbursty_lonely_downsample_min_samplesbursty_lonely_downsample_min_cell_quantilebursty_lonely_downsample_max_cell_quantilebursty_lonely_min_gene_totalbursty_lonely_min_gene_normalized_variancebursty_lonely_max_gene_similarityrare_max_genesrare_max_gene_cell_fractionrare_min_gene_maximumrare_genes_similarity_methodrare_genes_cluster_methodrare_min_genes_of_modulesrare_min_cells_of_modulesrare_max_cells_factor_of_random_pilerare_min_module_correlationrare_min_related_gene_fold_factorrare_max_related_gene_increase_factorrare_min_cell_module_totalrare_deviants_max_cell_fractionquick_and_dirtyselect_downsample_min_samplesselect_downsample_min_cell_quantileselect_downsample_max_cell_quantileselect_min_gene_relative_varianceselect_min_gene_totalselect_min_gene_top3select_min_genescells_similarity_log_datacells_similarity_value_regularizationcells_similarity_methodgroups_similarity_log_datagroups_similarity_methodknn_kcandidates_knn_k_size_factorpiles_knn_k_size_factorknn_k_umis_quantilemin_knn_kknn_balanced_ranks_factorknn_incoming_degree_factorknn_outgoing_degree_factorknn_min_outgoing_degreemarkers_knn_min_outgoing_degreemin_seed_size_quantilemax_seed_size_quantilecooldown_passcooldown_nodecooldown_phasecandidates_min_split_size_factorcandidates_max_merge_size_factordeviants_policydeviants_gap_skip_cellsdeviants_max_gap_cells_countdeviants_max_gap_cells_fractiondeviant_cells_regularization_quantiledeviants_min_gene_fold_factordeviants_min_compare_umisdeviants_min_noisy_gene_fold_factordeviants_max_gene_fractiondeviants_max_cell_fractiondissolve_min_robust_size_factorrare_dissolve_min_robust_size_factorrare_min_convincing_gene_fold_factordissolve_min_convincing_gene_fold_factordistinct_genes_countumap_max_marker_genesumap_ignore_lateral_genesumap_similarity_value_regularizationumap_similarity_log_dataumap_similarity_methodumap_min_distumap_spreadumap_kskeleton_kumap_fraction_regularizationspread_cover_fractionspread_noise_fractionquality_min_gene_totalmax_gbsproject_filter_rangesproject_ignore_range_quantileproject_ignore_range_min_overlap_fractionproject_min_query_markers_fractionproject_fold_regularizationproject_min_significant_gene_umisproject_candidates_countproject_min_candidates_fractionproject_min_usage_weightproject_max_projection_fold_factorproject_max_projection_noisy_fold_factorproject_max_consistency_fold_factorproject_log_dataoutliers_fold_regularizationignore_atlas_lateral_genesconsider_atlas_noisy_genesonly_atlas_marker_genesonly_query_marker_genesignore_query_lateral_genesconsider_query_noisy_genesmisfit_min_metacells_fractionmin_marker_metacells_gene_range_fold_factormetacells_gene_range_regularizationmin_marker_max_metacells_gene_fractionproject_renormalize_queryproject_correctionsproject_min_corrected_gene_correlationproject_min_corrected_gene_factortype_gene_normalized_variance_quantile
- Utilities
- Annotation
slice()copy_adata()set_name()get_name()set_m_data()get_m_data()set_o_data()get_o_series()get_o_numpy()get_o_names()maybe_o_numpy()set_v_data()get_v_series()get_v_numpy()get_v_names()maybe_v_numpy()set_oo_data()get_oo_frame()get_oo_proper()set_vv_data()get_vv_frame()get_vv_proper()set_oa_data()get_oa_frame()get_oa_proper()set_va_data()get_va_frame()get_va_proper()set_vo_data()get_vo_frame()get_vo_proper()has_data()- Computation
allow_inefficient_layout()to_layout()sort_compressed_indices()corrcoef()cross_corrcoef_rows()pairs_corrcoef_rows()logistics()cross_logistics_rows()pairs_logistics_rows()log_data()median_per()mean_per()nanmean_per()geomean_per()max_per()nanmax_per()min_per()nanmin_per()nnz_per()sum_per()sum_squared_per()rank_per()top_per()prune_per()quantile_per()nanquantile_per()scale_by()fraction_by()fraction_per()stdev_per()variance_per()normalized_variance_per()relative_variance_per()sum_matrix()nnz_matrix()mean_matrix()max_matrix()min_matrix()nanmean_matrix()nanmax_matrix()nanmin_matrix()rank_matrix_by_layout()bincount_vector()most_frequent()strongest()highest_weight()weighted_mean()fraction_of_grouped()downsample_matrix()downsample_vector()matrix_rows_folds_and_aurocs()sliding_window_function()patterns_matches()compress_indices()bin_pack()bin_fill()sum_groups()shuffle_matrix()cover_diameter()cover_coordinates()random_piles()represent()min_cut()sparsify_matrix()- Typing
CPP_DATA_TYPESShapedProperShapedImproperShapedMatrixProperMatrixNumpyMatrixCompressedMatrixImproperMatrixSparseMatrixPandasFrameVectorNumpyVectorImproperVectorPandasSeriesis_1d()is_2d()maybe_numpy_vector()maybe_numpy_matrix()maybe_sparse_matrix()maybe_compressed_matrix()maybe_pandas_frame()maybe_pandas_series()mustbe_numpy_vector()mustbe_numpy_matrix()mustbe_sparse_matrix()mustbe_compressed_matrix()mustbe_pandas_frame()mustbe_pandas_series()to_proper_matrix()to_proper_matrices()to_pandas_series()to_pandas_frame()frozen()freeze()unfreeze()unfrozen()to_numpy_matrix()to_numpy_vector()DENSE_FAST_FLAGSPARSE_FAST_FORMATSPARSE_SLOW_FORMATLAYOUT_OF_AXISPER_OF_AXISshaped_dtype()matrix_layout()is_layout()is_contiguous()to_contiguous()mustbe_canonical()is_canonical()eliminate_zeros()sort_indices()sum_duplicates()shaped_checksum()- Parallel
is_main_process()set_processors_count()get_processors_count()parallel_map()- Progress
progress_bar()progress_bar_slice()did_progress()has_progress_bar()start_progress_bar()end_progress_bar()start_progress_bar_slice()end_progress_bar_slice()- Timing
collect_timing()flush_timing()in_parallel_map()log_steps()timed_step()timed_call()timed_parameters()context()current_step()StepTimingCounters- Logging
setup_logger()logger()CALCSTEPPARAMlogged()top_level()log_return()logging_calc()log_calc()log_step()incremental()done_incrementals()cancel_incrementals()log_set()log_get()sizes_description()fractions_description()groups_description()mask_description()ratio_description()progress_description()fraction_description()fold_description()- Documentation
expand_doc()
- Scripts