norm.miR: ExiMiR low-level function for miRNA raw data normalization.
In ExiMiR: R functions for the normalization of Exiqon miRNA array data

Description Usage Arguments Details Value Author(s) See Also Examples

This function performs low-level normalization on an AffyBatch object and returns the result in a new AffyBatch object.

By default, it applies the spike-in probe-based normalization method. In case the spike-in probe-based method cannot be applied, a median normalization is executed instead. Several options allow however to force the execution of the spike-in probe-based normalization and to fine-tune the resulting correction functions.

norm.miR(abatch,
         normalize.method="spikein",
         normalize.param=list(),
         verbose=TRUE,
	 ...)

`abatch`	An `AffyBatch` object.
`normalize.method`	Character vector. It contains the name of normalization method. By default, the `spikein` method is used. Running `NormiR.normalize.methods(abatch)` indicates which other methods can be chosen, depending on the raw data contained in the `abatch` object.
`normalize.param`	A `R` list of the arguments that are used to control the `spikein` normalization. Running `NormiR.spikein.args()` provides a complete list of all the tunable parameters supported by `norm.miR` and explained below. figures.output Character vector. By default, `display` is used. Figures are shown to the screen. Using `file` generates the figures in PDF format in the working directory. min.corr Numeric. Default value is 0.5. Minimal allowed value for the average of the off-diagonal elements of the Pearson correlation matrix of the spike-in probeset intensities across the arrays. loess.span Numeric. Default value is -1, which corresponds to a loess smoothing neighbourhood spanning a fraction 3/(number of spike-in probesets) of the total number of points. Other positive values are allowed, see the `span` argument of the R `loess` function extrap.points Numeric. Default value is 2. The number of spike-in probesets used in the high-intensity extrapolation of the normalization correction function. extrap.method Character vector. Default value is `mean`. The method used for the high-intensity extrapolation of the normalization correction function. force.zero Logical. Default value is `FALSE`. If `TRUE`, it forces the normalization correction functions to have zero values at the lower end of the probe intensity range. cover.ext Numeric. Default value is 1/2. Minimal allowed relative coverage of the spike-in probesets intensities. It is computed as the ratio between the intensity range covered by the spike-in probes and the one covered by all probes on the array. cover.int Numeric. Default value is 1/3. Maximal allowed relative intensity interval between two consecutive spike-in probesets. It is computed as the largest intensity difference between two consecutive spike-in probesets divided by the overall probe intensity range. verbose Logical. Default is `TRUE`; some details are provided on the console. max.log2span Numeric. Default value is 1. Gives the maximal (log2) intensity interval allowed for the probes belonging to one spike-in probeset. probeset.list Vector of probes names that will be used as the "spike-in probes". By default, `norm.miR` uses the probes annotated as "spike-in" by Exiqon or Affymetrix.
`verbose`	Logical. The default value is `TRUE`. The details of the function execution are displayed on the console.
`...`	Any additional argument. Used for backward compatibility.

See accompanying vignette.

An AffyBatch object containing the normalized (but not summarized) expression data.

Sylvain.Gubian, Alain.Sewer, PMP SA

NormiR.normalize.methods, NormiR.spikein.args, NormiR.

data(galenv)
data(GSE20122)
GSE20122.normalized <- norm.miR(GSE20122,
                                normalize.param=list(figures.show=FALSE)) 
# Apply the affy method hist on the generated AffyBatch object GSE20122.normalized
layout(matrix(c(1,2), 1, 2, byrow = TRUE))
hist(GSE20122)
hist(GSE20122.normalized)
layout(1)