set_limma {benchdamic}R Documentation

set_limma

Description

Set the parameters for limma differential abundance detection method.

Usage

set_limma(
  pseudo_count = FALSE,
  design = NULL,
  coef = 2,
  norm = c("TMM", "TMMwsp", "RLE", "upperquartile", "posupperquartile", "none"),
  weights_logical = FALSE,
  expand = TRUE
)

Arguments

pseudo_count

add 1 to all counts if TRUE (default pseudo_count = FALSE).

design

character name of the metadata columns, formula, or design matrix with rows corresponding to samples and columns to coefficients to be estimated.

coef

integer or character index vector indicating which coefficients of the linear model are to be tested equal to zero.

norm

name of the normalization method used to compute the scaling factors to use in the differential abundance analysis. If norm is equal to "ratio", "poscounts", or "iterate" the normalization factors are automatically transformed into scaling factors.

weights_logical

logical vector, if TRUE a matrix of observational weights will be used for differential abundance analysis (default weights_logical = FALSE).

expand

logical, if TRUE create all combinations of input parameters (default expand = TRUE).

Value

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

See Also

DA_limma

Examples

# Set some basic combinations of parameters for limma
base_limma <- set_limma(design = ~ group, coef = 2)
# Set a specific set of normalization for limma (even of other packages!)
setNorm_limma <- set_limma(design = ~ group, coef = 2,
    norm = c("TMM", "poscounts"))
# Set many possible combinations of parameters for limma
all_limma <- set_limma(pseudo_count = c(TRUE, FALSE), design = ~ group,
    coef = 2, weights_logical = c(TRUE,FALSE))

[Package benchdamic version 1.0.0 Index]