SODEGIRpreprocessingGE {PREDA} | R Documentation

## Wrapper function for gene expression data preprocessing for SODEGIR analysis

### Description

Wrapper function for gene expression data preprocessing for SODEGIR analysis

### Usage

    SODEGIRpreprocessingGE(SampleInfoFile = NULL, CELfiles_dir = NULL,
    AffyBatchInput = NULL, custom_cdfname, arrayNameColumn = NULL,
    sampleNameColumn = NULL, classColumn,
    referenceGroupLabel, statisticType, optionalAnnotations = NULL,
    retain.chrs = NULL, reference_position_type = "median",
    testedTail = "both", singleSampleOutput = TRUE,
    varianceAll=FALSE)

### Arguments

`SampleInfoFile` | Path to sample info file
`CELfiles_dir` | Path to directory containing raw CEL data files for Affymetrix arrays
`AffyBatchInput` | Alternatively input raw data can be provided as an AffyBatch object. In this case sample classes will be inferred from phenodata contained in AffyBatch object. In particular classColumn parameter will refer to the column in pData(AffyBatchInput) object.
`custom_cdfname` | Specify the cdf library to be used for data preprocessing
`arrayNameColumn` | Column of sampleinfo file containing the name of raw data (CEL) files
`sampleNameColumn` | Column of sampleinfo file containing the name to be used for samples labels
`classColumn` | Column of sampleinfo file containing the label of sample classes. If input raw data are provided as an AffyBatch object, this parameter refers intead to the column in pData(AffyBatchInput) object.
`referenceGroupLabel` | Specify which class label is used for the reference sample used in computing statistics for differential expression.
`statisticType` | Stastistic for differential expression that is computed on input data. Possible values are "tstatistic", "FC" (Fold Change), "FCmedian" (fold change computed on medians)
`optionalAnnotations` | Character vector to select additional annotations fields to be included into the GenomicAnnotations object.
`retain.chrs` | Numeric vector, containing the list of chromosomes selected for the output GenomicAnnotations object. E.g. set retain.chrs=1:22 to limit the GenomicAnnotations object to chromosomes from 1 to 22. This might be ueseful to limit GenomiAnnotations objects to autosomic chromosomes.
`reference_position_type` | Specify which genomic coordinate must be used as reference position for PREDA analysis. Possible values are "start", "end", "median", "strand.start" or "strand.end". "strand.start" is strand specific start: i.e. start on positive strand but end on negative strand. "strand.end" is strand specific end.
`testedTail` | Specify what tail of the distribution will be tested for significantly extreme values in PREDA analysis. Possible values are "both", "upper" or "lower".
`singleSampleOutput` | Logical, if TRUE a statistic comparing each sample with the reference group is computed.
`varianceAll` | This parameter affect the computation only when singleSampleOutput is TRUE. varianceAll is itself a logical parameter. If TRUE, all pathological (e.g. tumor) samples and all normal (reference) samples are used to estimate variance in the comparison of individual pathological samples to the normal reference, as described in the original SODEGIR apper by Bicciato et al. (Nucleic Acids Res. 2009). The original SODEGIR statistic for Gene Expression was based on the SAM score. However, since July 2018 the original samr package is no more available in CRAN. Therefore in the current PREDA version the varianceAll=TRUE and singleSampleOutput=TREU can't be used with SAM. When singleSampleOutput is TRUE and a different statisticType is used, the variance is actually computed using only the normal (reference) samples. If FALSE (default value), the computation of statistics for single sample VS reference comparisons only take into account the variance in the reference group of samples.

### Details

Preprocess raw (CEL) files for Affymetrix gene expression arrays using user defined CDF libraries and RMA normalization.

Then statistics for differential expression are computed comparing each sample with the reference group.

Then annotations are retrieved from the corresponding annotation library.

Please note this function is a user-friendly preprocessing function for Affy gene expression microarrays. Step by step preprocessing functions can be used with any other platform.

### Value

A DataForPREDA object is returned.

### Author(s)

Francesco Ferrari

### References

Silvio Bicciato, Roberta Spinelli, Mattia Zampieri, Eleonora Mangano, Francesco Ferrari, Luca Beltrame, Ingrid Cifola, Clelia Peano, Aldo Solari, and Cristina Battaglia. A computational procedure to identify significant overlap of differentially expressed and genomic imbalanced regions in cancer datasets. Nucleic Acids Res, 37(15):5057-70, August 2009.

### See Also

`preprocessingGE`, `DataForPREDA`

### Examples

      ## Not run:
    require(PREDAsampledata)

    CELfilesPath <- system.file("sampledata", "GeneExpression",
    package = "PREDAsampledata")

    infofile <- file.path(CELfilesPath , "sampleinfoGE_PREDA.txt")

    SODEGIRGEDataForPREDA<-SODEGIRpreprocessingGE(SampleInfoFile=
    infofile,
    CELfiles_dir=CELfilesPath,
    custom_cdfname="hgu133plus2",
    arrayNameColumn=1,
    sampleNameColumn=2,
    classColumn="Class",
    referenceGroupLabel="normal",
    statisticType="tstatistic",
    optionalAnnotations=c("SYMBOL", "ENTREZID"),
    retain.chrs=1:22
    )

    ## End(Not run)

[Package PREDA version 1.36.0 Index]