adjustSignal {rCGH} | R Documentation

## Array-based CGH Preprocessing

### Description

This function performs several preprocessing steps: local regressions (loessFit) are used to correct cy3/cy5 and GC% bias, when Agilent dual-color hybridization are used only.
In case of Affymetrix cychp.txt (or cnchp.txt) data are used, these steps have been already done in ChAS or Affymetrix Power Tools.

### Usage

    ## S4 method for signature 'rCGH'
    adjustSignal(object, Scale=TRUE, Cy=TRUE, GC=TRUE, Ref="cy3",
        suppOutliers=TRUE, nCores=NULL, verbose=TRUE)

### Arguments

`object` | : An object of class `"rCGH"`
`Scale` | : logical. If `TRUE` (default), Log2Ratios are standardized.
`Cy` | : logical. If `TRUE` (default), cy3/cy5 bias is corrected using a local regression (loessFit). For Agilent dual-color hybridization only. Notice that, in case of Affymetrix files (cychp.txt or cnchp.txt), this argument is automatically set to `FALSE`, since this step is managed when files are exported from ChAS or APT.
`GC` | : logical. If `TRUE` (default), the GC% bias is corrected using a local regression (loessFit). For Agilent dual-color hybridization only. Notice that, in case of Affymetrix files (cychp.txt or cnchp.txt), this argument is automatically set to `FALSE`, since this step is managed when files are exported from ChAS or APT.
`Ref` | : string. Which cyanine was used as the reference. Possible values are "cy3" (default) and "cy5". For Agilent dual-color hybridization only.
`suppOutliers` | : logical. If `TRUE` (default), outliers are removed using an Expectation-Maximization algorithm (EM). See `details` below.
`nCores` | : numeric. The number of cores to use in order to speed up the computation. When `NULL` (default), half of the available cores are used. If a value greater than the number of available cores is passed, this latter will be used. See `detectCores`.
`verbose` | : logical. When `TRUE` (default), progress is printed.

### Details

When `suppOutliers` is `TRUE` (default), the Log2Ratios are splitted with respect to chromosomes. The main regions within each chromosome are identified using EM. Within each region r_i, x[r_i] values are redifined according to the corresponding model parameters. as:

x[r_i] ~ N(mu_i, sigma_i)

Notice that this step may substantially increase the computation time.

### Value

An object of class `"rCGH"`

### Author(s)

Frederic Commo

### See Also

`detectCores`, `mclapply`

### Examples

    filePath <- system.file("extdata", "Affy_cytoScan.cyhd.CN5.CNCHP.txt.bz2",
        package = "rCGH")
    cgh <- readAffyCytoScan(filePath, sampleName = "AffyScHD")
    cgh <- adjustSignal(cgh, nCores=1)
    getParam(cgh)

[Package rCGH version 1.16.0 Index]