kernelize {macat} | R Documentation

## Smooth expression values or scores

### Description

'kernelize' uses a kernel to smooth the data given in geneLocations by computing a weighted sum of the values vector. The weights for each position are given in the kernelweights matrix. A kernelweights matrix can be obtained by using the kernelmatrix function.

### Usage

    getsteps(geneLocations, step.width)
    kernelmatrix(steps, geneLocations, kernel, kernelparams)
    kernelize(values, kernelweights)

### Arguments

`geneLocations` | a list of gene locations (length n)
`step.width` | the width of steps in basepairs
`steps` | a list of locations where the kernelization shall be computed
`kernel` | kernel function one of rbf, kNN or basePairDistance (or your own)
`kernelparams` | a list of named parameters for the kernel (default is fitted to the data)
`values` | vector of length n or matrix (m x n) of values that are to be smoothed
`kernelweights` | a matrix of (n x steps) where n is the length of the values vector and steps is the number of points where you wish to interpolate

### Value

`getsteps` | a list of locations starting at min(genLocations) going to max(geneLocations) with steps of size step.width
`kernelmatrix` | a matrix of (n x steps) containing the kernel weights for each location in steps
`kernelize` | a vector of length steps or a matrix (m x steps) containing the smoothed values

### Author(s)

MACAT Development team

### See Also

`compute.sliding`, `evalScoring`

### Examples

      data(stjd)
      genes = seq(100)
      geneLocations = abs(stjd$geneLocation[genes])
      geneExpression = stjd$expr[genes,]
      step.width = 100000
      steps = getsteps(geneLocations, step.width)
      weights = kernelmatrix(steps, geneLocations, rbf, list(gamma=1/10^13))
      kernelized = kernelize(geneExpression, weights)
      plot(steps, kernelized[1,])

[Package macat version 1.2.0 Index]