SODEGIRpreprocessingGE: 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", "SAM" (SAM statistical score for differential expression), "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. Therefore in the current PREDA version the varianceAll=TRUE parameter can be used only for SAM statistic: 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.

Value

A DataForPREDA object is returned.

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.

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.

Examples

Run this code

  ## 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="gahgu133plus2",
# arrayNameColumn=1,
# sampleNameColumn=2,
# classColumn="Class",
# referenceGroupLabel="normal",
# statisticType="tstatistic",
# optionalAnnotations=c("SYMBOL", "ENTREZID"),
# retain.chrs=1:22
# )
# 
# 
#   ## End(Not run)

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