readMicroRnaAFE {AgiMicroRna} | R Documentation

## Read Agilent Feature Extraction txt data files

### Description

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

### Usage

    	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

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

    ## End(Not run)

[Package AgiMicroRna version 2.36.0 Index]