get_matrix_order: Return the hierarchical clustering order of a matrix

In metasnf: Meta Clustering with Similarity Network Fusion

Return the hierarchical clustering order of a matrix

Description

Return the hierarchical clustering order of a matrix

Usage

get_matrix_order(matrix, dist_method = "euclidean", hclust_method = "complete")

Arguments

matrix	Matrix to cluster.
dist_method	Distance method to use when calculating sorting order to of the matrix. Argument is directly passed into stats::dist. Options include "euclidean", "maximum", "manhattan", "canberra", "binary", or "minkowski".
hclust_method	Agglomerative method to use when calculating sorting order by stats::hclust. Options include "ward.D", "ward.D2", "single", "complete", "average", "mcquitty", "median", or "centroid".

Value

A numeric vector of the ordering derivied by the specified hierarchical clustering method applied to the provided matrix.

Examples

# dl <- data_list(
#     list(subc_v, "subcortical_volume", "neuroimaging", "continuous"),
#     list(income, "household_income", "demographics", "continuous"),
#     list(pubertal, "pubertal_status", "demographics", "continuous"),
#     list(anxiety, "anxiety", "behaviour", "ordinal"),
#     list(depress, "depressed", "behaviour", "ordinal"),
#     uid = "unique_id"
# )
# 
# sc <- snf_config(
#     dl = dl,
#     n_solutions = 20,
#     min_k = 20,
#     max_k = 50
# )
# 
# sol_df <- batch_snf(dl, sc)
# 
# ext_sol_df <- extend_solutions(
#     sol_df,
#     dl = dl,
#     min_pval = 1e-10 # p-values below 1e-10 will be thresholded to 1e-10
# )
# 
# # Calculate pairwise similarities between cluster solutions
# sol_aris <- calc_aris(sol_df)
# 
# # Extract hierarchical clustering order of the cluster solutions
# meta_cluster_order <- get_matrix_order(sol_aris)

metasnf documentation built on April 3, 2025, 5:40 p.m.