Package index • OAR

Wrapper Functions

These are all the functions you need to run the full analysis on your data.

oar(): Single line pipeline to run complete analysis
oar_by_factor(): Generate OAR score within each cluster and add them to full objects metadata
oar_deg(): Generate DEGs based on OAR score
get_pattern_genes(): Create list of which genes participate in each pattern.

Visualize results

A few convenient functions to visualize the results of your analysis.

scatter_score(): Create scatter plot of OAR score vs sparsity
oar_gcp_plot(): Plot identified gene co-expression patterns

Step-by-step functions

Run these in this order to achieve the same results as with the wrapper functions.

oar_preprocess_data(): Prepare data for oar fold functions
oar_hamming_distance(): Calculate hamming distances between genes
oar_patterns(): Identify gene co-expression patterns allowing for mismatch
oar_base(): Generate scores and p-values to determine transcriptional shifts

Utility functions

Called within other functions in the package.

pattern_pval_kw(): Kruskal-Wallis test to generate a per cell p-value based on gene co-expression patterns
oar_gene_graph(): Group gene co-expression patterns based on tolerance with a graph