| corr_coef {structToolbox} | R Documentation |
Calculates correlation between features and continuous variables.
corr_coef(alpha = 0.05, mtc = "fdr", factor_names, method = "spearman", ...)
alpha |
p-value threshold for determining significance. Default alpha = 0.05. |
mtc |
multiple test correction method to apply. Can be: holm, hochberg, hommel, bonferroni, BH, BY, fdr or none |
factor_names |
Sample_meta column names to correlate features with |
method |
'Calculate "kendall", "pearson" or "spearman" correlation coefficient. Default method = "spearman".' |
... |
additional slots and values passed to struct_class |
struct object
D = MTBLS79_DatasetExperiment(filtered=TRUE)
# subset for this example
D = D[,1:10]
# convert to numeric for this example
D$sample_meta$sample_order=as.numeric(D$sample_meta$sample_order)
D$sample_meta$sample_rep=as.numeric(D$sample_meta$sample_rep)
M = corr_coef(factor_names=c('sample_order','sample_rep'))
M = model_apply(M,D)