runSplits {benchdamic} | R Documentation |
Run the differential abundance detection methods on split datasets.
runSplits(split_list, method_list, normalization_list, object, verbose = TRUE)
split_list |
A list of 2 |
method_list |
a list object containing the methods and their parameters. |
normalization_list |
a list object containing the normalization method
names and their parameters produced by |
object |
a phyloseq object. |
verbose |
an optional logical value. If |
A named list containing the results for each method.
data(ps_plaque_16S) # Balanced design for independent samples my_splits <- createSplits( object = ps_plaque_16S, varName = "HMP_BODY_SUBSITE", balanced = TRUE, N = 10 # N = 100 suggested ) # Initialize some limma based methods my_limma <- set_limma(design = ~ HMP_BODY_SUBSITE, coef = 2, norm = c("TMM", "CSSmedian")) # Set the normalization methods according to the DA methods my_norm <- setNormalizations(fun = c("norm_edgeR", "norm_CSS"), method = c("TMM", "median")) # Run methods on split datasets results <- runSplits(split_list = my_splits, method_list = my_limma, normalization_list = my_norm, object = ps_plaque_16S)