get_highest_prune_param: Calculate the highest pruning parameter for the SNN graph...

In Core-Bioinformatics/ClustAssess: Tools for Assessing Clustering

Calculate the highest pruning parameter for the SNN graph given NN matrix

Description

Given a NN adjacency matrix, the function calculates the highest pruning parameter for the SNN graph that preserves the connectivity of the graph.

Usage

get_highest_prune_param(nn_matrix, n_neigh)

Arguments

nn_matrix	The adjacency matrix of the nearest neighbour graph.
n_neigh	The number of nearest neighbours.

Value

A list with the following fields:

• prune_value: The value of the highest pruning parameter.

• adj_matrix: The adjacency matrix of the SNN graph after pruning.

Note

Given the way the SNN graph is built, the possible values for the pruning parameter are limited and can be determined by the formula i / (2 * n_neigh - i), where i is a number of nearest neighbours between 0 and n_neigh.

Examples

set.seed(2024)
# create an artificial pca embedding
pca_embedding <- matrix(
    c(runif(100 * 10), runif(100 * 10, min = 3, max = 4)),
    nrow = 200, byrow = TRUE
)
rownames(pca_embedding) <- as.character(1:200)
colnames(pca_embedding) <- paste("PC", 1:10)

# calculate the nn adjacency matrix
nn_matrix <- getNNmatrix(
    RANN::nn2(pca_embedding, k = 5)$nn.idx,
    5,
    0,
    -1
)$nn

get_highest_prune_param(nn_matrix, 5)$prune_value

Core-Bioinformatics/ClustAssess documentation built on Nov. 14, 2024, 6:33 p.m.