dot-smoothMonotone: Monotone smoothing of the VST counts

In UMI4Cats: UMI4Cats: Processing, analysis and visualization of UMI-4C chromatin contact data

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.

UMI4Cats documentation built on Dec. 31, 2020, 2:01 a.m.