Takes the variance stabilized count values and calculates a symmetric monotone fit for the distance dependency. The signal trend is fitted using the fda package.
.smoothMonotone(trafo_counts, alpha = 20, penalty = 0.1, frag_data)
| trafo_counts | Variance stabilized count values assay from DDS object. |
|---|---|
| alpha | Approximate number of fragments desired for every basis function
of the B-spline basis. |
| penalty | Amount of smoothing to be applied to the estimated functional parameter. Default: 0.1. |
| frag_data | Data frame with all the information on restriction fragments and the interval around the viewpoint. |
A dataframe with monotone smoothed fit counts.
This function computes the smoothing function for the VST values, based on fda package, and calculates a symmetric monotone fit counts for the distance dependency