.smoothMonotone {UMI4Cats} | R Documentation

## Monotone smoothing of the VST counts

### Description

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.

### Usage

    .smoothMonotone(trafo_counts, alpha = 20, penalty = 0.1, frag_data)

### Arguments

`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. `floor((max(number of fragments)) / alpha)` is passed to `create.bspline.basis` as nbasis argument. 4 is the minimum allowed value. Default: 20.
`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.

### Details

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

### Value

A dataframe with monotone smoothed fit counts.

[Package UMI4Cats version 1.2.1 Index]