filterMicroRna {AgiMicroRna} | R Documentation |
Filter genes out according to their Quality Flag
filterMicroRna(ddNORM, dd, control, IsGeneDetected, wellaboveNEG, limIsGeneDetected, limNEG, makePLOT, targets, verbose, writeout)
ddNORM |
uRNAList with the Total Gene Signal in log2 scale to be FILTERED out according to a Quality FLAG |
dd |
uRNAList, containing the output from |
control |
logical, if |
IsGeneDetected |
logical, if |
wellaboveNEG |
logical, if |
limIsGeneDetected |
for a given feature xi accros samples, is the minimum in at least one experimental condition with a IsGeneDetected-FLAG = 1 (Is Detected) |
limNEG |
for a given feature xi accros samples, is the minimum in at least one experimental condition with intensity > Limit established for negative controls (Mean + 1.5 x SD) |
makePLOT |
logical, if |
targets |
data.frame with the targets structure |
verbose |
logical, if |
writeout |
logical, if |
Agilent Feature Extraction software provides a flag for each spot that identifies different quantification errors of the signal. Quantification flags were used to filter out signals that did not reach a minimum established criterion of quality.
The function returns a uRNAList containing the FILTERED data. In order to allow the tracking of those microRNAs that may have been filtered out from the original raw data, the following files are given:
NOCtrl\_exprs.txt: Log2 Normalized Total Gene Signals for the Non Control Genes NOCtrl\_FlagIsGeneDetected.txt: IsGeneDetected Flag for the Non Control Genes, 1 = detected IsNOTGeneDetected.txt: Genes that not are not detected according to IsGeneDetected Flag
Pedro Lopez-Romero
Agilent Feature Extraction Reference Guide http://www.Agilent.com
data(dd.micro,verbose=FALSE) data(targets.micro,verbose=FALSE) ddTGS=tgsMicroRna(dd.micro,half=TRUE,makePLOT=FALSE,verbose=FALSE) ddNORM=tgsNormalization(ddTGS,'quantile', makePLOTpre=FALSE,makePLOTpost=TRUE,targets.micro,verbose=FALSE) ddPROC=filterMicroRna(ddNORM, dd.micro, control=TRUE, IsGeneDetected=TRUE, wellaboveNEG=FALSE, limIsGeneDetected=50, limNEG=25, makePLOT=FALSE, targets.micro, verbose=FALSE, writeout=FALSE)