exprMat {coexnet} | R Documentation

## Calculate the expression matrix from the raw expression data.

### Description

This function use a affyBatch object with the raw expression data to normalize and transform the matrix from probeset to gene considering the option to remove the batch effect in the long microarray data.

### Usage

    exprMat(affy, genes, NormalizeMethod, SummaryMethod, BatchCorrect = TRUE)

### Arguments

`affy` | A AffyBatch object with the raw expression data.
`genes` | A table with two columns, in the firt one the name of each probe in the microarray with header "probe" and in the second one the corresponding gene or ID with header "ID".
`NormalizeMethod` | The method to normalize the raw data. Can be "vsn" to apply Variance Stabilizing Normalization function or "rma" to apply Robust Multi-Array Average function.
`SummaryMethod` | The method to pass from probeset to genes or ID. Can be "max" to selecto the probeset with the most average expression value or "median" to obtain the median of each sample of the set of probeset corresponding to particular gen or ID.
`BatchCorrect` | The option to apply batch effect correction, by default TRUE.

### Value

A SummarizedExperiment object with the expression matrix.

### Author(s)

Juan David Henao <judhenaosa@unal.edu.co>

### References

Huber, W., Von Heydebreck, A., Sultmann, H., Poustka, A., & Vingron, M. (2002). Variance stabilization applied to microarray data calibration and to the quantification of differential expression. Bioinformatics, 18(suppl 1), S96-S104.

Irizarry, R. A., Hobbs, B., Collin, F., Beazer Barclay, Y. D., Antonellis, K. J., Scherf, U., & Speed, T. P. (2003). Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics, 4(2), 249-264.

### See Also

`getAffy` to obtain the affyBatch object.

`geneSymbol` to obtain the data.frame with probeset and genes/ID from .SOFT file.

### Examples

    ## Not run:

    # Loading data

    if (require(affydata)) {
     data(Dilution)
    }

    # Loading table with probeset and gene/ID information

    data(info)

    # Calculating the expression matrix

    ## RMA

    rma <- exprMat(affy = Dilution,genes = info,NormalizeMethod = "rma",
    SummaryMethod = "median",BatchCorrect = FALSE)
    head(rma)

    ## VSN

    vsn <- exprMat(affy = Dilution,genes = info,NormalizeMethod = "vsn",
    SummaryMethod = "median",BatchCorrect = FALSE)
    head(vsn)

    ## End(Not run)

[Package coexnet version 1.2.0 Index]