bin_scdata              Bin genes by mean expression.
calculate_cvs           Compute mean expression level, standard
                        deviation and coefficient of variation of each
                        feature.
correlate_windows       Calculate correlations against top window.
correlations_to_densities
                        Transform the correlation table to density
                        distributions of correlation values
define_top_genes        Define the reference window using the most
                        highly expressed features.
determine_bin_cutoff    Determine a threshold for selecting bins of
                        features based on the metric table
filter_expression_table
                        Filter binned expression matrix
get_mean_median         Extract mean and median correlation coefficient
                        values
plot_correlations_distributions
                        Produce a density plot of correlation values
                        for each window of feature
plot_mean_variance      Produce a mean expression x coefficient of
                        variation scatter plot.
plot_metric             Produce a bar chart of mean (or median)
                        correlation coefficient per bin of feature.
plot_top_window_autocor
                        Utility plot to choose a top_window size
scData_hESC             Expression data from 32 human embryonic stem
                        cells
sc_feature_filter       Filter scRNA-seq expression matrix to keep only
                        highly informative features. Integrated
                        pipeline.
