Checks potential confounders in the metadata and produces some visualizations
check.confounders(siamcat, fn.plot, meta.in = NULL, feature.type='filtered', verbose = 1)
an object of class siamcat-class
string, filename for the pdf-plot
vector, specific metadata variable names to analyze, defaults to NULL (all metadata variables will be analyzed)
string, on which type of features should the function
work? Can be either
integer, control output:
Does not return anything, but outputs plots to specified pdf file
This function checks for associations between class labels and potential confounders (e.g. Age, Sex, or BMI) that are present in the metadata. Statistical testing is performed with Fisher's exact test or Wilcoxon test, while associations are visualized either as barplot or Q-Q plot, depending on the type of metadata.
Additionally, it evaluates associations among metadata variables using conditional entropy and associations with the label using generalized linear models, producing a correlation heatmap and appropriate quantitative barplots, respectively.
# Example data data(siamcat_example) # Simple working example check.confounders(siamcat_example, './conf_plot.pdf')#>#> #>#>