compute.sliding {macat} | R Documentation

## Compute and plot smoothing of expression values or scores along the chromosome

### Description

'compute.sliding' computes a smoothing of the expression data or scores along the chromosome using the specified kernel function. This function is also used within the 'evalScoring' function. 'plotSliding' creates a plot of the smoothed expression values / scores.

### Usage

    compute.sliding(data, chromosome, sample, kernel, kernelparams=NULL, step.width = 1e+06)
    plotSliding(data, chromosome, sample, kernel, kernelparams=NULL,
    step.width=1000000, ...)

### Arguments

`data` | A MACATData list holding the Expression values and gene locations
`chromosome` | the chromosome to be smoothed
`sample` | the sample (patient) whose expression values are smoothed
`kernel` | a kernel function (one of rbf, kNN, basePairDistance or your own)
`kernelparams` | a list of named parameters for the kernel (by default estimated from the data)
`step.width` | the smoothing is computed stepwise every step.width basepairs (default is 100000)
`...` | futher graphical parameters passed on to `plot.default`

### Value

for `compute.sliding`: a matrix of dimension (steps x 2) with in the first column the locations in basepairs where an interpolation is computed, and in the second column the smoothed values. `plotSliding` does not return anything and is merely called for its side-effect producing the plot.

### Author(s)

MACAT development team

### See Also

`kernelize`, `evalScoring`

### Examples

    data(stjd)
    # just compute smoothed values:
    smooth = compute.sliding(stjd, chromosome=3, sample=6, rbf,
                             kernelparams=list(gamma=1/10^13))
    # compute and plot smoothed values:
    plotSliding(stjd, chromosome=3, sample=6,rbf,
                kernelparams=list(gamma=1/10^13),pch=20,
                main="Chromosome 3")

[Package macat version 1.10.0 Index]