omicverse.single.pyVIA

omicverse.single.pyVIA(adata: AnnData, adata_key: str = 'X_pca', adata_ncomps: int = 80, basis: str = 'X_umap', clusters: str = '', dist_std_local: float = 2, jac_std_global=0.15, labels: ndarray = None, keep_all_local_dist='auto', too_big_factor: float = 0.4, resolution_parameter: float = 1.0, partition_type: str = 'ModularityVP', small_pop: int = 10, jac_weighted_edges: bool = True, knn: int = 30, n_iter_leiden: int = 5, random_seed: int = 42, num_threads=-1, distance='l2', time_smallpop=15, super_cluster_labels: bool = False, super_node_degree_list: bool = False, super_terminal_cells: bool = False, x_lazy: float = 0.95, alpha_teleport: float = 0.99, root_user=None, preserve_disconnected: bool = True, dataset: str = '', super_terminal_clusters: list = [], is_coarse=True, csr_full_graph: ndarray = '', csr_array_locally_pruned='', ig_full_graph='', full_neighbor_array='', full_distance_array='', df_annot=None, preserve_disconnected_after_pruning: bool = False, secondary_annotations: list = None, pseudotime_threshold_TS: int = 30, cluster_graph_pruning_std: float = 0.15, visual_cluster_graph_pruning: float = 0.15, neighboring_terminal_states_threshold=3, num_mcmc_simulations=1300, piegraph_arrow_head_width=0.1, piegraph_edgeweight_scalingfactor=1.5, max_visual_outgoing_edges: int = 2, via_coarse=None, velocity_matrix=None, gene_matrix=None, velo_weight=0.5, edgebundle_pruning=None, A_velo=None, CSM=None, edgebundle_pruning_twice=False, pca_loadings=None, time_series=False, time_series_labels: list = None, knn_sequential: int = 10, knn_sequential_reverse: int = 0, t_diff_step: int = 1, single_cell_transition_matrix=None, embedding_type: str = 'via-mds', do_compute_embedding: bool = False, color_dict: dict = None, user_defined_terminal_cell: list = [], user_defined_terminal_group: list = [], do_gaussian_kernel_edgeweights: bool = False, RW2_mode: bool = False, working_dir_fp: str = '/home/shobi/Trajectory/Datasets/') → None

VIA-based trajectory inference and lineage visualization wrapper.