- Pathway and Network Analysis 95
- Sample selection
At this stage, you are getting interested in the tumor biology of acute
lymphoblastic leukemia (ALL) with different kinds of molecular genetic
abnormalities. There were several metadata delineating additional clinical
information in the ExpressionSet object ALL. ALL$BT shows you the
types of leukemic lymphocytes (B or T cells) with the stages of diseases
(1–4). ALL$mol indicates whether these leukemic samples harbored some
common genetic abnormalities, such as BCR−ABL4,5(representative of the
Philadelphia chromosome^6 ) or ALL1−AF4^7 fusion genes. Here, you want to
compare B cell leukemia with BCR−ABL rearrangement and B cell leukemia
with ALL1−AF4 rearrangement, and fetch the relevant sample indices as
follows:
bCell<- grep(“ˆB”, as.character(ALL$BT))
bcrAbl<-which(ALL$mol==“BCR/ABL”)
all1Af4<-which(ALL$mol==“ALL1/AF4”)
You can then take intersections between bCell and bcrAbl, and between bCell
and all1Af4 as well as select the corresponding gene expression matrices from
DATA.ALL, respectively:
data.bcrabl<- DATA.ALL[, intersect(bCell, bcrAbl)]
data.all1Af4<- DATA.ALL[, intersect(bCell, all1Af4)]
You can get the number of samples and rename these samples as follows:
N.bcrabl<- ncol(data.bcrabl)
N.all1Af4<- ncol(data.all1Af4)
colnames(data.bcrabl)<- paste(“BCR/ABL”, 1:N.bcrabl , sep=“”)
colnames(data.all1Af4)<- paste(“ALL1/AF4”, 1:N.all1Af4, sep=“”)
- Analysis of differentially expressed genes
In this step, we apply a method called Significant Analysis of Microarray
(SAM)^8 to B cell leukemia with BCR/ABL or ALL1/AF4 rearrangement
and find out the differentially expressed (DE) genes between them. Here, you
can use the R package samr, which is able to implement several functions
necessary for SAM. Before taking advantage of the function samr(), you can
prepare the input format for this function:
library(samr)
mergedData<- cbind(data.bcrabl, data.all1Af4)
classLabel<- c(rep(1, N.bcrabl), rep(2, N.all1Af4))