runDA: runDA

In mcalgaro93/benchdamic: Benchmark of differential abundance methods on microbiome data

runDA

Description

Run the differential abundance detection methods.

Usage

runDA(method_list, object, weights = NULL, verbose = TRUE)

Arguments

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 TRUE, information about the steps of the algorithm is printed. Default verbose = TRUE.

Value

A named list containing the results for each method.

Examples

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", "CSS"))

# Run the methods
results <- runDA(method_list = my_methods, object = ps)

mcalgaro93/benchdamic documentation built on Nov. 23, 2024, 5:06 p.m.