Recent changes to Code

Code modified by Alexandra Jauhiainen

Alexandra Jauhiainen — Tue, 15 Apr 2014 09:05:21 -0000

--- v4
+++ v5
@@ -10,7 +10,7 @@

 ##

-> contrast.matrix <- makeContrasts(K01-Wt, K02-Wt, K03-Wt,K04-Wt,K05-Wt,K06-Wt, + K07-Wt,K08-Wt,K09-Wt,K10-Wt, levels=design)
+> contrast.matrix <- makeContrasts(K01-Wt, K02-Wt, K03-Wt,K04-Wt,K05-Wt,K06-Wt,K07-Wt,K08-Wt,K09-Wt,K10-Wt, levels=design)
 > fit2 <- contrasts.fit(fit, contrast.matrix)
 > fit2 <- eBayes(fit2) # moderated t-statistics

Code modified by Alexandra Jauhiainen

Alexandra Jauhiainen — Wed, 22 May 2013 17:35:05 -0000

--- v3
+++ v4
@@ -54,7 +54,7 @@
 > data(Layered)
 > m<-nrow(infMatr)
 > p<-ncol(infMatr)
-> o <- getOrderings(infMatr[,1:m],1000,50,name="LayeredNet")
+> o <- getOrderings(infMatr\[,1:m],1000,50,name="LayeredNet")
 > DAGlkhds<-DAGsFromOrders(exprDat,o,infWgt=infMatr,infConf=0.8)
 > res<-consensusNet(DAGlkhds,nbest=5,thresh=0.25)
 > estAdj <- res[[1]]$adjMat

Code modified by Alexandra Jauhiainen

Alexandra Jauhiainen — Wed, 22 May 2013 17:34:05 -0000

--- v2
+++ v3
@@ -21,7 +21,7 @@

 ##

-infMatrix <- influencePlot(pvalMatrix,c(1e-6,seq(0.001,0.3,0.005)))
+> infMatrix <- influencePlot(pvalMatrix,c(1e-6,seq(0.001,0.3,0.005)))

 ##

@@ -39,6 +39,7 @@
 > adjMatrix

 ##
+
 > measures<-accMeasures(adjMatrix,goldAdjMatrix)
 > measures

@@ -48,3 +49,14 @@
 > V(g)$name <- colnames(adjMatrix);V(g)$label <- V(g)$name
 > plot(g)

+##
+
+> data(Layered)
+> m<-nrow(infMatr)
+> p<-ncol(infMatr)
+> o <- getOrderings(infMatr[,1:m],1000,50,name="LayeredNet")
+> DAGlkhds<-DAGsFromOrders(exprDat,o,infWgt=infMatr,infConf=0.8)
+> res<-consensusNet(DAGlkhds,nbest=5,thresh=0.25)
+> estAdj <- res[[1]]$adjMat
+> a1 <- accMeasures(estAdj,goldAdj)
+> a2 <- accMeasures(rbind(estAdj,matrix(0,59,100)),rbind(goldAdj,matrix(0,59,100)))

Code modified by Alexandra Jauhiainen

Alexandra Jauhiainen — Wed, 22 May 2013 17:22:49 -0000

--- v1
+++ v2
@@ -1,4 +1,50 @@
-
 > library(ripe)
 > library(limma)
 > data(DREAM4)
+
+##
+
+> design <- model.matrix(~ 0+factor(rep(1:11,each=5)))
+> colnames(design) <- unique(colnames(pertData))
+> fit <- lmFit(pertData,design)
+
+##
+
+> contrast.matrix <- makeContrasts(K01-Wt, K02-Wt, K03-Wt,K04-Wt,K05-Wt,K06-Wt, + K07-Wt,K08-Wt,K09-Wt,K10-Wt, levels=design)
+> fit2 <- contrasts.fit(fit, contrast.matrix)
+> fit2 <- eBayes(fit2) # moderated t-statistics
+
+##
+
+> pvalMatrix<-t(fit2$p.value)
+> diag(pvalMatrix)<-NA
+
+##
+
+infMatrix <- influencePlot(pvalMatrix,c(1e-6,seq(0.001,0.3,0.005)))
+
+##
+
+> ords <- getOrderings(infMatrix,1000,25,name="insilico_size10_1")
+
+
+##
+> DAGScores <- DAGsFromOrders(ssData,ords,infWgt=infMatrix)
+
+##
+
+> nbest <- ceiling(length(DAGScores$lklhds)*c(0.1,0.2,0.3))
+> out <- consensusNet(DAGScores,nbest=nbest)
+> adjMatrix <- out[[3]]$adjMat
+> adjMatrix
+
+##
+> measures<-accMeasures(adjMatrix,goldAdjMatrix)
+> measures
+
+##
+
+> g <- graph.adjacency(adjMatrix)
+> V(g)$name <- colnames(adjMatrix);V(g)$label <- V(g)$name
+> plot(g)
+

Code modified by Alexandra Jauhiainen

Alexandra Jauhiainen — Wed, 22 May 2013 15:32:50 -0000

library(ripe)
library(limma)
data(DREAM4)