FourCSeq (version 1.6.2)

getZScores: Calculate z-scores using the residuals of the general trend fit.

Description

getZScores calculates the z-score for each fragment within a distance from the viewpoint defined by distAroundVP. For the calculation the count data is first transformed with a variance stabilizing transformation from the DESeq2 package. The decay trend of this transformed data with distance from the viewpoint is fitted either with local regression model using locfit or a monotone decay fit using the fda package. z-scores are finally calculated from the residuals of the fit values.

Usage

getZScores(object, removeZeros = TRUE, minCount = 40, minDist = NULL, fitFun = "distFitMonotoneSymmetric", sdFun = mad, ...)

Arguments

object

A FourC object.

removeZeros

Parameter to define if fragments with zero counts across all replicates and conditions should be removed from the calculation. Default is TRUE.

minCount

The minimum median count value across replicates, a fragment has to have to be used for the calculation of z-scores. Default is 40

minDist

Define a minimum distance to both sides of the viewpoint that is discarded for analysis. If undefined (NULL), the borders of the viewpoint peak are estimated as the minimum values next to the viewpoint before the signal rises again.

fitFun

Fit function to be used. Either distFitMonotoneSymmetric (default), distFitMonotone or any self-defined function to fit the distance dependency.

sdFun

Function to calculate the variation of the data. Default is mad.

...

Additional Parameters passed to the distance fit function specified in fitFun (e.g. distFitMonotone, distFitMonotoneSymmetric).

Value

Returns a FourC object for the selected viewpoint with z-score values for all fragments on the viewpoint chromosome that passed the minCount threshold and that were not too close to the viewpoint. All additional required data is saved in the object. Especially the following information is added to the FourC object:

1. metadata: parameters passed to the getZScore function.
2. colData: sdFun values calculated from the fit residuals
3. rowRanges: the distance information to the viewpoint and information calculated for the variance stabilizing data are added.
4. assays: variance stabilized count values (trafo), fit values (fit), z-score values (zScore), associated p-values (pValue) and adjusted p-values (pAdjusted)

See Also

FourC, countFragmentOverlaps, distFitMonotone, distFitMonotoneSymmetric

Examples

data(fc, package="FourCSeq")

fcf <- getZScores(fc)

fcf