R/find_rho_and_var.R
run_cor_bootstrap.Rd
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.
run_cor_bootstrap(
x,
n_it = 20L,
nThreads = 1L,
verbose = TRUE,
iterations_gap = 1L
)
Numeric matrix, the gene expression matrix to analyse. Genes are in columns, samples are in rows.
Integer, number of bootstrap iterations
Integer, number of threads to use for computations
Logical, should progress be printed?
If output is verbose - Number of iterations between
each status message
(Default=1 - Displayed only if verbose=TRUE
)
A list with two fields
Numeric matrix constaining the bootstrapped mean of the Spearman correlation between each column
Numeric matrix constaining the bootstrapped variance of the Spearman correlation between each column
data("normal_expression")
cor_res <- run_cor_bootstrap(
x = normal_expression,
n_it = 100, nThreads = 2L
)
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