IDDIRR | R Documentation |
Calculates the gain or the loss of differentially expressed genes due to meta-analysis compared to individual studies.
IDDIRR(finalde, deindst)
finalde |
Vector of indices of differentially expressed genes after meta-analysis |
deindst |
Vector of indices of differentially expressed genes found at least in one study |
DE |
Number of Differentially Expressed (DE) genes |
IDD |
Integration Driven Discoveries: number of genes that are declared DE in the meta-analysis that were not identified in any of the individual studies alone. |
Loss |
Number of genes that are declared DE in individual studies but not in meta-analysis. |
IDR |
Integration-driven Discovery Rate: proportion of genes that are identified as DE in the meta-analysis that were not identified in any of the individual studies alone. |
IRR |
Integration-driven Revision Rate: percentage of genes that are declared DE in individual studies but not in meta-analysis. |
Guillemette Marot
Marot, G., Foulley, J.-L., Mayer, C.-D., Jaffrezic, F. (2009) Moderated effect size and p-value combinations for microarray meta-analyses. Bioinformatics. 25 (20): 2692-2699.
data(Singhdata) out=EScombination(esets=Singhdata$esets,classes=Singhdata$classes) IDDIRR(out$Meta,out$AllIndStudies) ## The function is currently defined as #function(finalde,deindst) #{ #DE=length(finalde) #gains=finalde[which(!(finalde %in% deindst))] #IDD=length(gains) #IDR=IDD/DE*100 #perte=which(!(deindst %in% finalde)) #Loss=length(perte) #IRR=Loss/length(deindst)*100 #res=c(DE,IDD,Loss,IDR,IRR) #names(res)=c("DE","IDD","Loss","IDR","IRR") #res #}
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