calculateScaleSpace: Calculate scale-space representation for given 4C-seq data

In walter-ca/Scale4C: Scale4C: an R/Bioconductor package for scale-space transformation of 4C-seq data

Description

Scale4C uses Gauss kernels of increasing (square) sigma to smooth the original 4C-seq signal. The resulting data is stored in a 2D matrix (position x sigma).

Usage

calculateScaleSpace(data, maxSQSigma = 5000)

Arguments

data	Scale-space object for the 4C-seq data
maxSQSigma	Maximum square sigma used to calculate the scale space

Details

The central idea of the scale-space transformation is to smooth the original signal with increasing strength, identify inflection points, track those inflection points throughout the different smoothing layers, and find singularities in those inflection point 'lines'. In case of 4C-seq data, this corresponds to smoothing the signal gradually, while making notes when features such as 'peaks' or 'valleys' disappear by merging with other features. calculateScaleSpace smoothes the original signal up to a provided smoothing factor square sigma (Gauss kernel).

Value

A SummarizedExperiment that contains in its first assay the scale space representation for a Scale4C object

Author(s)

Carolin Walter

Examples

    # read prepared example data
    data(liverData)
    # use small maxSQSigma for a fast example
    scaleSpace(liverData)<-calculateScaleSpace(liverData, maxSQSigma = 10)
    head(t(assay(scaleSpace(liverData), 1))[,1:20])

walter-ca/Scale4C documentation built on May 5, 2019, 9:03 p.m.