confounders_clsq {structToolbox} | R Documentation |
Compares the coefficients for a ttest without including confounding factors to models with confounding factor included. Currently only ttest is supported.
confounders_clsq( alpha = 0.05, mtc = "fdr", factor_name, confounding_factors, threshold = 0.15, ... )
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_name |
the column name of sample_meta to use in regression |
confounding_factors |
the column names of factors potentially confounding with the main factor if interest |
threshold |
the threshold (between 0 and 1) for accepting a factor as confounding |
... |
additional slots and values passed to struct_class |
A struct model object with functions for applying classical least squares
struct object
D = MTBLS79_DatasetExperiment() M = filter_by_name(mode='include',dimension='variable', names=colnames(D$data)[1:10]) + # first 10 features filter_smeta(mode='exclude',levels='QC', factor_name='class') + # reduce to two group comparison confounders_clsq(factor_name = 'class', confounding_factors=c('sample_order','batch')) M = model_apply(M,D)