calc_differential_radiomics: Perform differential radiomic analysis
In cgplab/RadAR: Radiomic Analysis with R

Description Usage Arguments Value Author(s)

This function implements two non-parametric statistical tests (Wilcoxon-Mann-Whitney and AUC) to perform differential analysis of radiomic features. In case of Wilcoxon-Mann-Whitney p-values can be adjusted using different methods.

calc_differential_radiomics(
  rdr = NULL,
  conditions = NULL,
  which_data = "scaled",
  method = "wilcox",
  adjust_pvalues_by = "BH",
  thr_pvalue = NA,
  thr_auc = NA
)

`rdr`	A RadAR object (class `SummarizedExperiment`).
`conditions`	(numeric, character) Vector of labels for each sample in rdr. Should have the same length of `ncol(rdr)`. Required.
`which_data`	(character) Which data use for plot. It can be one of the following: "normal", "scaled", "normalized".
`method`	(character) Which statistical methods use for differential analysis. It can be "wilcox" (Wilcoxon-Mann-Whitney), "auc" (Area Under the Curve) or "kruskal-wallis".
`adjust_pvalues_by`	(character) Which method use to correct p-values from wilcox test. Print available methods by `p.adjust.methods`.
`thr_pvalue`	(numeric) P-value threshold to identify statistically significant features for wilcox or kruskal-wallis. It should be in the range (0, 1].
`thr_auc`	(numeric) AUC threshold to identify statistically significant features. It should be in the range (0.5,1].