check.confounders: Check for potential confounders in the metadata

In zellerlab/siamcat: Statistical Inference of Associations between Microbial Communities And host phenoTypes

Check for potential confounders in the metadata

Description

Checks potential confounders in the metadata and visualize the results

Usage

check.confounders(siamcat, fn.plot, meta.in = NULL,
feature.type='filtered', verbose = 1)

Arguments

siamcat	an object of class siamcat-class
fn.plot	string, filename for the pdf-plot
meta.in	vector, specific metadata variable names to analyze, defaults to NULL (all metadata variables will be analyzed)
feature.type	string, on which type of features should the function work? Can be either c()"original", "filtered", or "normalized"). Please only change this paramter if you know what you are doing!
verbose	integer, control output: 0 for no output at all, 1 for only information about progress and success, 2 for normal level of information and 3 for full debug information, defaults to 1

Details

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.

Please note that the confounder check is currently only available for binary classification problems!

Value

Does not return anything, but outputs plots to specified pdf file

Examples

# Example data
data(siamcat_example)

# Simple working example
check.confounders(siamcat_example, './conf_plot.pdf')

zellerlab/siamcat documentation built on Feb. 1, 2024, 2:21 a.m.