learn_diff_meth: Learn differential methylation profiles using BLM
In andreaskapou/mpgex: Methylation Profiles predict Gene Expression

learn_diff_meth learns differential methylation profiles and returns the fitted coefficients using the Basis Linear Model.

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learn_diff_meth(control, treatment, diff_basis, fit_feature = NULL,
  lambda = 0, x_eval = 50, is_parallel = is_parallel,
  no_cores = no_cores)

`control`	The optimized values for the control samples.
`treatment`	The optimized values for the treatment samples.
`diff_basis`	The basis object for differential methylation.
`fit_feature`	Additional feature on how well the profile fits the methylation data.
`lambda`	The regularization parameter when fitting the BLM.
`x_eval`	Integer denoting the number of evaluation points.
`is_parallel`	Logical, indicating if code should be run in parallel.
`no_cores`	Number of cores to be used, default is max_no_cores - 1.