runDA {benchdamic} | R Documentation |
Run the differential abundance detection methods.
runDA(method_list, object, weights = NULL, verbose = TRUE)
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.
set.seed(1) # Create a very simple phyloseq object counts <- matrix(rnbinom(n = 60, size = 3, prob = 0.5), nrow = 10, ncol = 6) metadata <- data.frame("Sample" = c("S1", "S2", "S3", "S4", "S5", "S6"), "group" = as.factor(c("A", "A", "A", "B", "B", "B"))) ps <- phyloseq::phyloseq(phyloseq::otu_table(counts, taxa_are_rows = TRUE), phyloseq::sample_data(metadata)) # Set some simple normalizations my_norm <- setNormalizations() # Add them to the phyloseq object ps <- runNormalizations(normalization_list = my_norm, object = ps) # Set some limma instances my_methods <- set_limma(design = ~ group, coef = 2, norm = c("TMM", "poscounts", "CSSmedian")) # Run the methods results <- runDA(method_list = my_methods, object = ps)