set_edgeR {benchdamic}R Documentation

set_edgeR

Description

Set the parameters for edgeR differential abundance detection method.

Usage

set_edgeR(
  pseudo_count = FALSE,
  group_name = NULL,
  design = NULL,
  robust = FALSE,
  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).

group_name

character giving the name of the column containing information about experimental group/condition for each sample/library.

design

character or formula to specify the model matrix.

robust

logical, should the estimation of prior.df be robustified against outliers?

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 observation weights must be supplied (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_edgeR method.

See Also

DA_edgeR

Examples

# Set some basic combinations of parameters for edgeR
base_edgeR <- set_edgeR(group_name = "group", design = ~ group, coef = 2)

# Set a specific set of normalization for edgeR (even of other packages!)
setNorm_edgeR <- set_edgeR(group_name = "group", design = ~ group, coef = 2,
    norm = c("TMM", "poscounts"))

# Set many possible combinations of parameters for edgeR
all_edgeR <- set_edgeR(pseudo_count = c(TRUE, FALSE), group_name = "group",
    design = ~ group, robust = c(TRUE, FALSE), coef = 2,
    weights_logical = c(TRUE,FALSE))

[Package benchdamic version 1.0.0 Index]