Standardize covars matrix only once

[AsafManela]

dmr and hdmr calls by default standardize the covars matrix, because they call fit(GammaLassoPath,...) on each column of counts, which standardizes its X (=covars) matrix upon entry by default.
This means we are needlessly repeating this Lasso.standardizeX call multiple times. See relevant part of Lasso.jl

A better solution would:

1. check for the keyword argument standardize in dmr/hdmr calls
2. standardize if requested before calling fit(GammaLassoPath,...) with standardize=false, keeping track of Xnorm
3. multiply coefs by Xnorm as in [Lasso.jl] (https://github.com/JuliaStats/Lasso.jl/blob/55718966db53679e333d8a94749e8722b082796c/src/coordinate_descent.jl#L847). Specifically,
   3.1 If returning DMRCoefs/HDMRCoefs (called with dmr/hdmr), then we only keep the coeffcients, so just multiply these in place by Xnorm
   3.2 If returning DMRPaths/HDMRPaths (called with dmrpaths/hdmrpaths), then we need to modify path.coefs for each path.