set_edgeR {benchdamic} | R Documentation |
Set the parameters for edgeR differential abundance detection method.
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 )
pseudo_count |
add 1 to all counts if TRUE (default
|
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 |
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 |
weights_logical |
logical vector, if true a matrix of observation
weights must be supplied (default |
expand |
logical, if TRUE create all combinations of input parameters
(default |
A named list containing the set of parameters for DA_edgeR
method.
# 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))