set_NOISeq: set_NOISeq

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

set_NOISeq

Description

Set the parameters for NOISeq differential abundance detection method.

Usage

set_NOISeq(
  assay_name = "counts",
  pseudo_count = FALSE,
  contrast = NULL,
  norm = c("rpkm", "uqua", "tmm", "n"),
  expand = TRUE
)

Arguments

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.
pseudo_count	add 1 to all counts if TRUE (default pseudo_count = FALSE).
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.
norm	name of the normalization method to use in the differential abundance analysis. Choose between the native edgeR normalization methods, such as TMM, TMMwsp, RLE, upperquartile, posupperquartile, or none. Alternatively (only for advanced users), if norm is equal to "ratio", "poscounts", or "iterate" from norm_DESeq2, "CSS" from norm_CSS, or "TSS" from norm_TSS, the scaling factors are automatically transformed into normalization factors. If custom factors are supplied, make sure they are compatible with edgeR normalization factors.
expand	logical, if TRUE create all combinations of input parameters (default expand = TRUE).

Value

A named list containing the set of parameters for DA_NOISeq method.

See Also

DA_NOISeq

Examples

# Set a basic combination of parameters for NOISeq with 'tmm' normalization
base_NOISeq <- set_NOISeq(pseudo_count = FALSE, norm = "tmm",
    contrast = c("group", "B", "A"), expand = FALSE)
# try many normalizations
many_NOISeq <- set_NOISeq(pseudo_count = FALSE, 
    norm = c("tmm", "uqua", "rpkm", "n"), contrast = c("group", "B", "A"))

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