Nothing
options(width=2000)
argv = commandArgs(TRUE);
print(argv)
print(paste("length=",length(argv),sep=""))
mode<-as.numeric(argv[1])
print(c("mode =", mode))
#########################################################################
# (user-define 1) you got to redefine this according different study!!!!
#########################################################################
filename2id.1<-function(x) {
y1<-unlist(strsplit(x,"\\_"))[1]
y2<-unlist(strsplit(y1,"\\."))[1]
return(y2)
}
# nimh (use csv file =c("filename","ggirID"))
filename2id.2<-function(x) {
d<-read.csv("./postGGIR/inst/example/filename2id.csv",head=1,stringsAsFactors=F)
y1<-which(d[,"filename"]==x)
if (length(y1)==0) stop(paste("Missing ",x," in filename2id.csv file",sep=""))
if (length(y1)>=1) y2<-d[y1[1],"newID"]
return(as.character(y2))
}
#########################################################################
# main call
#########################################################################
call.afterggir<-function(mode,rmDup=FALSE,filename2id=filename2id.1){
library(postGGIR)
#################################################
# (user-define 2) Fill in parameters of your ggir output
#################################################
currentdir =
studyname =
bindir =
outputdir =
epochIn = 5
epochOut = 5
flag.epochOut = 60
use.cluster = FALSE
log.multiplier = 9250
QCdays.alpha = 7
QChours.alpha = 16
useIDs.FN<-NULL
setwd(currentdir)
#########################################################################
# remove duplicate sample IDs for plotting and feature extraction
#########################################################################
if (mode==3 & rmDup){
# step 1: read ./summary/*remove_temp.csv file (output of mode=2)
keep.last<-TRUE #keep the latest visit for each sample
sumdir<-paste(currentdir,"/summary",sep="")
setwd(sumdir)
inFN<-paste(studyname,"_samples_remove_temp.csv",sep="")
useIDs.FN<-paste(sumdir,"/",studyname,"_samples_remove.csv",sep="")
#################################################
# (user-define 3 as rmDup=TRUE) create useIDs.FN file
#################################################
# step 2: create the ./summary/*remove.csv file manually or by R commands
d<-read.csv(inFN,head=1,stringsAsFactors=F)
d<-d[order(d[,"Date"]),]
d<-d[order(d[,"newID"]),]
d[which(is.na(d[,"newID"])),]
S<-duplicated(d[,"newID"],fromLast=keep.last) #keep the last copy for nccr
d[S,"duplicate"]<-"remove"
write.csv(d,file=useIDs.FN,row.names=F)
}
#########################################################################
# maincall
#########################################################################
setwd(currentdir)
afterggir(mode=mode,useIDs.FN,currentdir,studyname,bindir,
outputdir,epochIn,epochOut,flag.epochOut,log.multiplier,use.cluster,QCdays.alpha=QCdays.alpha,QChours.alpha=QChours.alpha, filename2id=filename2id)
}
##############################################
call.afterggir(mode)
##############################################
# Note: call.afterggir(mode=0)
# mode =0 : creat sw/Rmd file
# mode =1 : data transform using cluster or not
# mode =2 : summary
# mode =3 : clean
# mode =4 : impu
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.