calculate_distance: Functions to calculate distance matrices using cpu computing

In GSgalgoR: An Evolutionary Framework for the Identification and Study of Prognostic Gene Expression Signatures in Cancer

Description

Functions to calculate distance matrices using cpu computing

Usage

calculate_distance_pearson_cpu(x)

calculate_distance_spearman_cpu(x)

calculate_distance_uncentered_cpu(x)

calculate_distance_euclidean_cpu(x)

select_distance(distancetype = "pearson")

Arguments

x	an expression matrix with features as rows and samples as columns
distancetype	a character that can be either 'pearson', 'uncentered', 'spearman' or 'euclidean'

Value

select_distance(distancetype) assigns global function calculate_distance according to the parameters specified

calculate_distance_pearson_cpu(x) returns columnwise pearson distance calculated using the CPU

calculate_distance_uncentered_cpu(x) returns columnwise uncentered pearson distance calculated using the CPU

calculate_distance_spearman_cpu(x) returns columnwise spearman distance calculated using the CPU

calculate_distance_euclidean_cpu(x) returns columnwise euclidean distance calculated using the CPU

Author(s)

Martin E Guerrero-Gimenez, [e-mail]

Examples

# load example dataset
require(iC10TrainingData)
require(pamr)

data(train.Exp)

calculate_distance <- select_distance(distancetype = "pearson")
Dist <- calculate_distance(train.Exp)
k <- 4
Pam <- cluster_algorithm(Dist, k)
table(Pam$cluster)

GSgalgoR documentation built on Nov. 8, 2020, 6:57 p.m.