calculate_distance {GSgalgoR} | R Documentation

## Functions to calculate distance matrices using cpu computing

### 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, mguerrero@mendoza-conicet.gob.ar

### 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)

[Package GSgalgoR version 1.2.1 Index]