Package index • scregclust

Setting up and performing clustering

Functions to prepare the input data and to perform single-cell regulatory-driven clustering.

scregclust(): Uncover gene modules and their regulatory programs from single-cell data

scregclust_format(): Package data before clustering

Plotting and evaluation

Functions which help in plotting and evaluating results.

plot_module_count_helper(): Plot average silhouette scores and average predictive \(R^2\)

plot_regulator_network(): Plotting the regulatory table from scregclust as a directed graph

plot_silhouettes(): Plot individual silhouette scores

Utility functions

Functions that make accessing aspects of the results easier.

get_avg_num_regulators(): Get the average number of active regulators per module

get_num_final_configs(): Return the number of final configurations

get_rand_indices(): Compute Rand indices

get_regulator_list(): Return list of regulator genes

get_target_gene_modules(): Extract target gene modules for given penalization parameters

Other helpers

available_results(): Extract final configurations into a data frame

cluster_overlap(): Create a table of module overlap for two clusterings

fast_cor(): Fast computation of correlation

find_module_sizes(): Determine module sizes

kmeanspp(): Perform the k-means++ algorithm