DA_Maaslin2: DA_Maaslin2

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

DA_Maaslin2

Description

Fast run for Maaslin2 differential abundance detection method.

Usage

DA_Maaslin2(
  object,
  assay_name = "counts",
  normalization = c("TSS", "CLR", "CSS", "NONE", "TMM"),
  transform = c("LOG", "LOGIT", "AST", "NONE"),
  analysis_method = c("LM", "CPLM", "ZICP", "NEGBIN", "ZINB"),
  correction = "BH",
  random_effects = NULL,
  fixed_effects = NULL,
  contrast = NULL,
  reference = NULL,
  verbose = TRUE
)

Arguments

object	a phyloseq or TreeSummarizedExperiment object.
assay_name	the name of the assay to extract from the TreeSummarizedExperiment object (default assayName = "counts"). Not used if the input object is a phyloseq.
normalization	The normalization method to apply.
transform	The transform to apply.
analysis_method	The analysis method to apply.
correction	The correction method for computing the q-value.
random_effects	The random effects for the model, comma-delimited for multiple effects.
fixed_effects	The fixed effects for the model, comma-delimited for multiple effects.
contrast	character vector with exactly, three elements: a string indicating the name of factor whose levels are the conditions to be compared, the name of the level of interest, and the name of the other level.
reference	The factor to use as a reference for a variable with more than two levels provided as a string of 'variable,reference' semi-colon delimited for multiple variables.
verbose	an optional logical value. If TRUE, information about the steps of the algorithm is printed. Default verbose = TRUE.

Value

A list object containing the matrix of p-values 'pValMat', a matrix of summary statistics for each tag 'statInfo', and a suggested 'name' of the final object considering the parameters passed to the function.

See Also

Maaslin2.

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))
# Differential abundance
DA_Maaslin2(object = ps, normalization = "CLR", transform = "NONE",
    analysis_method = "LM", correction = "BH", random_effects = NULL,
    fixed_effects = "group", contrast = c("group", "B", "A"),
    verbose = FALSE)

mcalgaro93/benchdamic documentation built on March 10, 2024, 10:40 p.m.