- Pathway and Network Analysis 101
Figure 3. Gene correlation network for B cell leukemia with BCR−ABL rearrangement.
Also, you can plot a correlation graph in BCR/ABL samples (N=37) for
these DE genes under|PCC|> 0 .4 (corresponding to a two-tailed P-value =
0.014; see Fig. 3):
eMat<- data.bcrabl[rownames(data.bcrabl) %in% c(up.4.fold, dn.4.fold),]
rownames(eMat)<- sapply(strsplit(rownames(eMat), “\/”), “[”)[1,]
eSet<- new(“ExpressionSet”, exprs=eMat)
corrG<- compCorrGraph(eSet, tau=0.4)
edgemode(corrG)<-“undirected”
plot(corrG)
- Summary and perspective
In this chapter, you have learned some techniques about pathway and
network analysis to clearly see the genomic differences between B cell
leukemia with ALL1−AF4 and BCR−ABL rearrangements. With more