readMicroRnaAFE: Read Agilent Feature Extraction txt data files

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

Description

Read the data files generated by the Agilent Feature Extraction image analysis software

Usage

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	readMicroRnaAFE(targets,verbose=FALSE)

Arguments

targets

A data frame that specifies experimental conditions under which each sample has been obtained.

verbose

logical, if TRUE prints out output

Details

The function reads the *.txt files generated by the AFE Software using the 'read.maimages' function of 'limma' package.

Data, colected with the Agilent Feature Extraction Software, are stored in a uRNAList object with the following components:

- dd.micro\$TGS 'gTotalGeneSignal' - dd.micro\$TPS 'gTotalProbeSignal' - dd.micro\$meanS 'gMeanSignal' - dd.micro\$procS 'gProcessedSignal' - dd.micro\$targets 'targets' - dd.micro\$genes\$ProbeName 'Probe Name' - dd.micro\$genes\$GeneName 'microRNA Name' - dd.micro\$genes\$ControlType 'FLAG to specify the sort of feature' - dd.micro\$other\$gIsGeneDetected 'FLAG IsGeneDetected' - dd.micro\$other\$gIsSaturated 'FLAG IsSaturated' - dd.micro\$other\$gIsFeatNonUnifOL 'FLAG IsFeatNonUnifOL' - dd.micro\$other\$gIsFeatPopnOL 'FLAG IsFeatPopnOL' - dd.micro\$other\$gBGMedianSignal 'gBGMedianSignal' - dd.micro\$other\$gBGUsed 'gBGUsed'

Value

A uRNAList containing the following elements:

uRNAList\$TGS

matrix, 'gTotalGeneSignal'

uRNAList\$TPS

matrix, 'gTotalProbeSignal'

uRNAList\$meanS

matrix, 'gMeanSignal'

uRNAList\$procS

matrix, 'gProcessedSignal'

uRNAList\$targets

data.frame, 'FileName'

uRNAList\$genes\$ProbeName

character, 'AGilent Probe Name'

uRNAList\$genes\$GeneName

character, 'microRNA Name'

uRNAList\$genes\$ControlType

integer, '0'= Feature, '1'= Positive control, '-1'= Negative control

uRNAList\$other\$gIsGeneDetected

matrix, FLAG to classify signal if 'IsGeneDetected=1' or 'not=0'

uRNAList\$other\$gIsSaturated

matrix, FLAG to classify signal if 'IsSaturated = 1' or 'not=0'

uRNAList\$other\$gIsFeatPopnOL

matrix, FLAG to classify signal if 'IsFeatPopnOL = 0' or 'not=1'

uRNAList\$other\$gIsFeatNonUnifOL

matrix, FLAG to classify signal if 'gIsFeatNonUnifOL = 0' or 'not=1'

uRNAList\$other\$gBGMedianSignal

matrix, gBGMedianSignal

uRNAList\$other\$gBGUsed

matrix, gBGUsed

Author(s)

Pedro Lopez-Romero

References

Agilent Feature Extraction Reference Guide http://www.Agilent.com

Smyth, G. K. (2005). Limma: linear models for microarray data. In: 'Bioinformatics and Computational Biology Solutions using R and Bioconductor'. R. Gentleman, V. Carey, S. Dudoit, R. Irizarry, W. Huber (eds), Springer, New York, pages 397–420.

See Also

A data example can be found in dd.micro See also readTargets to see how to build the target file and the example given in targets.micro

Examples

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## Not run: 
data(targets.micro)
dd.micro = readMicroRnaAFE(targets.micro)

## End(Not run)


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