API

Import pilotpy as:

import pilotpy

tools: `tl`

Trajectory & Clusters Analysis

`tl.wasserstein_distance`(adata[, emb_matrix, ...])	Calculate the Wasserstein (W) distance among samples using PCA representation and clustering information.
`tl.cell_importance`(adata[, width, height, ...])	Order cells based on estimated time and visualize cell type importance.
`tl.genes_importance`(adata, name_cell[, col, ...])	Order genes based on estimated time and visualize gene importance.
`tl.gene_cluster_differentiation`(adata[, ...])	Perform gene cluster differentiation analysis.
`tl.results_gene_cluster_differentiation`([...])	Retrieve and sort gene cluster statistics based on specified criteria.
`tl.compute_diff_expressions`(adata[, ...])	Using limma R package, lmFit fits a linear model using weighted least squares for each gene.

plot: `pl`

plots

`pl.heatmaps`(adata[, figsize, col_cluster, ...])	Plot heatmaps of cost matrix and Wasserstein distances.
`pl.trajectory`(adata[, n_evecs, epsilon, ...])	Find trajectories using Diffusion Maps and visualize the trajectory plot.
`pl.fit_pricipla_graph`(adata[, NumNodes, ...])	Fit an Elastic Principal Graph to the data and extract pseudotime information.
`pl.go_enrichment`(df[, num_gos, source, ...])	Perform Gene Ontology (GO) enrichment analysis and create a scatterplot of enriched terms.
`pl.exploring_specific_genes`([cluster_name, ...])	Explore specific genes within a cluster to analyze their patterns in comparison to other cell types.
`pl.genes_selection_heatmap`(adata, cell_type)	Parameters adata ad.AnnData DESCRIPTION. cell_type str DESCRIPTION. filter_table_feature str, optional DESCRIPTION. The default is 'R-squared'. filter_table_feature_pval str, optional DESCRIPTION. The default is 'adjusted P-value'. table_filter_thr float, optional DESCRIPTION. The default is 0.05. table_filter_pval_thr float, optional DESCRIPTION. The default is 0.05. cluster_method str, optional DESCRIPTION. The default is 'complete'. cluster_metric str, optional DESCRIPTION. The default is 'correlation'. scaler_value float, optional DESCRIPTION. The default is 0.4. cmap_color str, optional DESCRIPTION. The default is 'RdBu_r'. figsize tuple, optional DESCRIPTION. The default is (7, 9). fontsize int, optional DESCRIPTION. The default is 14. path_to_results str, optional DESCRIPTION. The default is 'Results_PILOT/'.
`pl.plot_hallmark_genes_clusters`(adata, cell_type)	Parameters adata ad.AnnData DESCRIPTION. cell_type str DESCRIPTION. gene_set_library str, optional DESCRIPTION. The default is 'MSigDB_Hallmark_2020'. cmap str, optional DESCRIPTION. The default is 'coolwarm'. font_size int, optional DESCRIPTION. The default is 14.
`pl.plot_gene_list_pattern`(gene_list, cell_type)	Parameters gene_list list DESCRIPTION. cell_type str DESCRIPTION. sample_col str, optional DESCRIPTION. The default is 'sampleID'. time_col str, optional DESCRIPTION. The default is 'Time_score'. path_to_results str, optional DESCRIPTION. The default is 'Results_PILOT/'. plot_color str, optional DESCRIPTION. The default is 'tab:orange'. points_color str, optional DESCRIPTION. The default is 'viridis'. fontsize TYPE, optional DESCRIPTION. The default is 14.