runMocks {benchdamic} | R Documentation |
Run the differential abundance detection methods on mock datasets.
runMocks(mocks, method_list, object, weights = NULL, verbose = TRUE)
mocks |
a |
method_list |
a list object containing the methods and their parameters. |
object |
a phyloseq object. |
weights |
an optional numeric matrix giving observational weights. |
verbose |
an optional logical value. If |
A named list containing the results for each method.
# Load some data data(ps_stool_16S) # Generate the pattern for 10 mock comparisons # (N = 1000 is suggested) mocks <- createMocks(nsamples = phyloseq::nsamples(ps_stool_16S), N = 10) head(mocks) # Add some normalization/scaling factors to the phyloseq object my_norm <- setNormalizations(fun = c("norm_edgeR", "norm_CSS"), method = c("TMM", "median")) ps_stool_16S <- runNormalizations(normalization_list = my_norm, object = ps_stool_16S) # Initialize some limma based methods my_limma <- set_limma(design = ~ group, coef = 2, norm = c("TMM", "CSSmedian")) # Run methods on mock datasets results <- runMocks(mocks = mocks, method_list = my_limma, object = ps_stool_16S)