fsEdger selects features using the exactTest function
from the edgeR package. This function does not normalize the data,
but does estimate dispersion using the estimateCommonDisp
and estimateTagwiseDisp functions.
fsEdger(object, top = 0, keep = 0, ...)An ExprsArray object to undergo feature selection.
A numeric scalar or character vector. A numeric scalar indicates
the number of top features that should undergo feature selection. A character vector
indicates specifically which features by name should undergo feature selection.
Set top = 0 to include all features. A numeric vector can also be used
to indicate specific features by location, similar to a character vector.
A numeric scalar. Specifies the number of top features that should get
returned by the feature selection method. Use of keep is generally not
recommended, but can speed up analyses of large data.
Arguments passed to the detailed function.
Returns an ExprsArray object.
The user can normalize the data before feature selection using the
modTMM function. Note that applying edgeR to already normalized
counts differs slightly from applying edgeR with normalization.