run_cor_bootstrap {csdR} | R Documentation

## Run bootstrapping of Spearman correlations within a dataset

### Description

This function provides the more low-level functionality of bootstrapping the Spearman correlations of the columns within a dataset. Only use this function if you want a low-level interface, else `run_csd` provides a more streamlined approach if you want to do a CSD analysis.

### Usage

    run_cor_bootstrap(
      x,
      n_it = 20L,
      nThreads = 1L,
      verbose = TRUE,
      iterations_gap = 1L
    )

### Arguments

`x` | Numeric matrix, the gene expression matrix to analyse. Genes are in columns, samples are in rows.
`n_it` | Integer, number of bootstrap iterations
`nThreads` | Integer, number of threads to use for computations
`verbose` | Logical, should progress be printed?
`iterations_gap` | If output is verbose - number of iterations after issue a status message (Default=1 - displayed only if verbose=TRUE)

### Value

A list with two fields

rho

  Numeric matrix constaining the bootstrapped mean of the Spearman correlation between each column

var

  Numeric matrix constaining the bootstrapped variance of the Spearman correlation between each column

### Examples

    data("normal_expression")
    cor_res <- run_cor_bootstrap(
        x = normal_expression,
        n_it = 100, nThreads = 2L
    )

[Package csdR version 1.0.0 Index]