DA.sam: SAMSeq

In Russel88/DAtest: Comparing Differential Abundance/Expression Methods

SAMSeq

Description

SAMSeq implementation for DAtest

Usage

DA.sam(
  data,
  predictor,
  paired = NULL,
  fdr.output = 0.05,
  allResults = FALSE,
  ...
)

Arguments

data	Either a matrix with counts/abundances, OR a phyloseq object. If a matrix/data.frame is provided rows should be taxa/genes/proteins and columns samples
predictor	The predictor of interest. Factor or Numeric, OR if data is a phyloseq object the name of the variable in sample_data(data) in quotation
paired	For paired/blocked experimental designs. Either a Factor with Subject/Block ID for running paired/blocked analysis, OR if data is a phyloseq object the name of the variable in sample_data(data) in quotation
fdr.output	Passed to SAMseq. (Approximate) False Discovery Rate cutoff for output in significant genes table
allResults	If TRUE will return raw results from the SAMseq function
...	Additional arguments for the SAMseq function

Value

A data.frame with with results.

Examples

# Creating random count_table and predictor
set.seed(4)
mat <- matrix(rnbinom(1000, size = 0.1, mu = 500), nrow = 100, ncol = 10)
rownames(mat) <- 1:100
pred <- c(rep("Control", 5), rep("Treatment", 5))

# Running SamSeq
res <- DA.sam(data = mat, predictor = pred)

Russel88/DAtest documentation built on March 24, 2022, 3:50 p.m.