DA_basic | R Documentation |
Fast run for basic differential abundance detection methods such as wilcox and t tests.
DA_basic( object, assay_name = "counts", pseudo_count = FALSE, contrast = NULL, test = c("t", "wilcox"), paired = FALSE, verbose = TRUE )
object |
a phyloseq or TreeSummarizedExperiment object. |
assay_name |
the name of the assay to extract from the
TreeSummarizedExperiment object (default |
pseudo_count |
add 1 to all counts if TRUE (default
|
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. |
test |
name of the test to perform. Choose between "t" or "wilcox". |
paired |
boolean. Choose whether the test is paired or not (default
|
verbose |
an optional logical value. If |
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.
DA_Seurat
for a similar implementation of basic
tests.
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_basic(object = ps, pseudo_count = FALSE, contrast = c("group", "B", "A"), test = "t", verbose = FALSE)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.