Thanks very much for your kindly reply.
Actually, I want a sliding window for purposes chromosome expression pattern mining. My research microorganism is a plant pathogen, Gibberella zeae, and I first used SAS to divide locus number with 10, 20, 30, or 40 on the fungal chromosome according to their location. I really want to see whether among the continual 10, 20, 30, or 40 locus has some expression pattern that different from rest genes. Because I know sigPathway (R package, pathway analysis with microarray data) can do this kind of job. What I use SAS to do is to subset locus in arbitrary genes numbers, such as 10, 20, 30, 40, or so on, and I hope to use sigPathway to analysis whether these genes chromosome location have effect on its gene expression.
When I use sigpathway to analyze my microarray data, it made my compute out of memory. I have tried the following R codes in several computer, but it always the same, even it computing more than one day, it can not get any results. Would you please point out my problem and give me some suggestions? Thank you very much.
I attach my microarray data and R codes in the attachment, and I hope you can have a look.
#the following code is for annotation list initiation.
setwd("C:/analysis data and codes")
x <- read.table("chr1.txt",header=FALSE,sep="\t")
attach(x)
x$group <- paste(V2,V3,sep="_")
group <- x$group
y <- data.frame(group,V2,V3,V4)
xx <- as.list(group)
xx <- xx[!is.na(xx)]
xx <- unlist(xx)
xxUnique <- unique(xx)
yy <- vector("list",length(xxUnique))
for(i in 1:length(yy))
{
MT <- "MT_lab"
yy[[i]] <- list(src=MT,title=xxUnique[i],probes=as.character(y[group==xxUnique[i],]$V4))
}
#the following code is for sigpathway analysis.
library(sigPathway)
YANG <- read.table("All microarray MT_LAB.txt",header=T,sep="t")
attach(YANG)
Y <- data.frame(TF134_1_3DAK,TF134_2_3DAK,WT1_3DAK,WT2_3DAK,row.names=locus_no)
p <- c("1_trt","1_trt","0_norm","0_norm")
statList <- calcTStatFast(Y,p,ngroups=2)
hist(statList$pval,breaks=seq(0,1,0.025),xlab="p-value",ylab="Frequency",main="")
set.seed(1234)
YANG <- runSigPathway(yy,20,500,Y,p,nsim=100,weightType="constant",ngroup=2,npath=25,verbose=F,allpathway=F,alwaysUseRandomPerm=F)
write.table(YANG$df.pathways[1:25,],quote=F,sep="t",file="chr1_sig.txt")
YANG$list.gPS[[1]]
save.image("chr1_sig")
please, define DFR
The tool is available at this URL http://geneexplorer.mc.vanderbilt.edu/digmap This is not a perl script, this is a JAVA program.
DFR is about differential flag regions by visual inspection or computational method (DFR mapping).Yes, DIGMAP is a JAVA program, but this article also mentioned about perl script. Because this software only can analyze data from human and mouse, it can not provide help for my microarray data, which is come from a plant pathogen Gibberella zeae. So I have to use perl script to do myself. Would you please have a look of my new poster below and give me some suggestions? Thank you very much!