Welcome to SCIV’s documentation!

SCIV: Unveiling the pivotal cell types involved in variant function regulation at a single-cell resolution.

We propose SCIV, a method integrating cell cluster-type correction with a weighted seed-based random walk. By eliminating substantial noise from seed cells, SCIV enables the efficient enrichment of causal variants within cells of interest.

Contents

• 1. SCIV usage
  • 1.1 Standard pipeline
    • 1.1.1 Import library and environment setup
    • 1.1.2 Download example files
    • 1.1.3 Run SCIV
  • 1.2 SCIV execution process for each step
• 2. SCIV API
  • Download (.dl)
    • download_sc_atac_file()
    • download_trait_file()
    • download_trs_file()
    • download_trs_score_file()
    • read_sc_atac_file()
    • read_trait_file()
    • read_trs_file()
    • read_trs_score_file()
  • File (.fl)
    • barcodes_add_anno()
    • read_barcodes_file()
    • read_h5()
    • read_h5ad()
    • read_pkl()
    • read_sc_atac()
    • read_sc_atac_10x_h5()
    • read_variants()
    • save_h5()
    • save_h5ad()
    • save_pkl()
    • to_fragments()
    • to_meta()
  • Model (.ml)
    • association_score()
    • core()
    • knock()
  • Plot (.pl)
    • Graph
      • communities_graph()
      • graph()
      • network_two_types()
    • Heatmap
      • heatmap()
      • heatmap_annotation()
    • Scatter
      • manhattan_causal_variant()
      • pseudo_time_score()
      • scatter_3d()
      • scatter_atac()
      • scatter_base()
      • scatter_trait()
      • volcano_base()
    • Violin
      • violin_base()
      • violin_trait()
    • Box
      • box_base()
      • box_trait()
    • KDE
      • kde()
    • Line
      • base_line()
    • Bar
      • bar()
      • bar_significance()
      • bar_trait()
      • class_bar()
      • rate_bar_plot()
      • two_bar()
    • Barcode
      • barcode_base()
      • barcode_trait()
    • Pie
      • base_pie()
      • pie_label()
      • pie_trait()
    • Bubble
      • bubble()
    • Radar
      • base_radar()
      • radar()
      • radar_trait()
      • rate_circular_bar_plot()
    • Venn
      • three_venn()
      • two_venn()
  • Preprocessing (.pp)
    • adata_group()
    • adata_map_df()
    • filter_data()
    • get_difference_genes()
    • get_difference_peaks()
    • get_gene_enrichment()
    • get_gene_expression()
    • get_peak_matrix()
    • get_sc_atac()
    • get_tf_data()
    • gsea_enrichr()
    • merge_sc_atac()
    • paga_trajectory()
    • poisson_vi()
  • Tool (.tl)
    • Algorithm
      • add_bernoulli_fluctuation_noise()
      • add_noise_perturb()
      • ami()
      • ari()
      • binary_indicator()
      • calculate_fragment_weighted_accessibility()
      • calculate_init_score_weight()
      • calinski_harabasz()
      • coefficient_of_variation()
      • davies_bouldin()
      • euclidean_distances()
      • is_asc_sort()
      • jaccard_similarity()
      • k_means()
      • kl_divergence()
      • lsi()
      • marginal_normalize()
      • mean_symmetric_scale()
      • min_max_norm()
      • obtain_cell_cell_network()
      • overlap()
      • overlap_sum()
      • pca()
      • perturb_data()
      • safe_kl_divergence()
      • semi_mutual_knn_weight()
      • sigmoid()
      • silhouette()
      • spectral_clustering()
      • spectral_eigenmaps()
      • symmetric_scale()
      • tf_idf()
      • tsne()
      • umap()
      • z_score_marginal()
      • z_score_normalize()
      • z_score_to_p_value()
    • Random Walk
      • RandomWalk
        • RandomWalk.run_ablation_m_knn()
        • RandomWalk.run_ablation_ncsw()
        • RandomWalk.run_ablation_ncw()
        • RandomWalk.run_ablation_nsw()
        • RandomWalk.run_benchmark()
        • RandomWalk.run_core()
        • RandomWalk.run_en_ablation_m_knn()
        • RandomWalk.run_en_ablation_ncsw()
        • RandomWalk.run_en_ablation_ncw()
        • RandomWalk.run_en_ablation_nsw()
        • RandomWalk.run_enrichment()
        • RandomWalk.run_knock()
        • RandomWalk.scale_norm()
      • TraitDataParallel
        • TraitDataParallel.gather()
        • TraitDataParallel.scatter()
      • random_walk()
      • trs_scale_norm()
    • Matrix
      • down_sampling_data()
      • matrix_callback_block_storage()
      • matrix_division_block_storage()
      • matrix_dot_block_storage()
      • matrix_multiply_block_storage()
      • matrix_operation_memory_efficient()
      • merge_matrix()
      • split_matrix()
      • vector_multiply_block_storage()
  • Util (.ul)
    • check_adata_get()
    • check_gpu_availability()
    • file_method()
    • generate_hex_colors()
    • generate_str()
    • get_index()
    • get_real_predict_label()
    • list_duplicate_set()
    • list_index()
    • log()
    • merge_matrix()
    • numerical_bisection_step()
    • set_inf_value()
    • split_matrix()
    • strings_map_numbers()
    • sum_min_max()
    • to_dense()
    • to_sparse()
    • track_with_memory()