set_MAST {benchdamic} | R Documentation |
Set the parameters for MAST differential abundance detection method.
set_MAST( pseudo_count = FALSE, rescale = c("median", "default"), design = NULL, coefficient = NULL, norm = "TSS", expand = TRUE )
pseudo_count |
add 1 to all counts if TRUE (default
|
rescale |
Rescale count data, per million if 'default', or per median library size if 'median' ('median' is suggested for metagenomics data). |
design |
The model for the count distribution. Can be the variable name, or a character similar to "~ 1 + group", or a formula, or a 'model.matrix' object. |
coefficient |
The coefficient of interest as a single word formed by the variable name and the non reference level. (e.g.: 'ConditionDisease' if the reference level for the variable 'Condition' is 'control'). |
norm |
name of the normalization method used to compute the
normalization factors to use in the differential abundance analysis. If
|
expand |
logical, if TRUE create all combinations of input parameters
(default |
A named list containing the set of parameters for DA_MAST
method.
# Set some basic combinations of parameters for MAST base_MAST <- set_MAST(design = ~ group, coefficient = "groupB") # Set a specific set of normalization for MAST (even of other packages!) setNorm_MAST <- set_MAST(design = ~ group, coefficient = "groupB", norm = c("TSS", "poscounts", "TMM")) # Set many possible combinations of parameters for MAST all_MAST <- set_MAST(pseudo_count = c(TRUE, FALSE), rescale = c("median", "default"), design = ~ group, coefficient = "groupB", norm = c("TSS", "poscounts"))