Hi Ana,
My guess is that in your second code fragment you are assigning the
rownames of "a" and the _values_ contained in a$blup to the data.table
"data". As I don't have much experience with data tables I may be
wrong, but I suspect that the column name "blup" may not be visible or
even present in "data". I don't see it in "dd" above this code
fragment.
Jim
On Wed, Dec 16, 2020 at 11:12 AM Ana Marija <sokovic.anamar...@gmail.com> wrote:
>
> Hello,
>
> I made a terribly inefficient code which runs forever but it does run.
>
> library(dplyr)
> library(splitstackshape)
>
> datalist = list()
> files <- list.files("/WEIGHTS1/Retina", pattern=".RDat", ignore.case=T)
>
> for(i in files)
> {
> a<-get(load(i))
> names <- rownames(a)
> data <- as.data.frame(cbind(names,a))
> rownames(data) <- NULL
> dd=na.omit(concat.split.multiple(data = data, split.cols = c("names"),
> seps = ":"))
> dd=select(dd,names_1,blup,names_3,names_4)
> colnames(dd)=c("rsid","weight","ref_allele","eff_allele")
> dd$WGT<-i
> datalist[[i]] <- dd # add it to your list
> }
>
> big_data = do.call(rbind, datalist)
>
> There is 17345 RDat files this loop has to go through. And each file
> has approximately 10,000 lines. All RDat files can be downloaded from
> here: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE115828 and
> they are compressed in this file: GSE115828_retina_TWAS_wgts.tar.gz .
> And subset of 3 of those .RDat files is here:
> https://github.com/montenegrina/sample
>
> For one of those files, say i="retina.ENSG00000135776.wgt.RDat"
> dd looks like this:
>
> > head(dd)
> rsid weight ref_allele eff_allele
> 1: rs72763981 9.376766e-09 C G
> 2: rs144383755 -2.093346e-09 A G
> 3: rs1925717 1.511376e-08 T C
> 4: rs61827307 -1.625302e-08 C A
> 5: rs61827308 -1.625302e-08 G C
> 6: rs199623136 -9.128354e-10 GC G
> WGT
> 1: retina.ENSG00000135776.wgt.RDat
> 2: retina.ENSG00000135776.wgt.RDat
> 3: retina.ENSG00000135776.wgt.RDat
> 4: retina.ENSG00000135776.wgt.RDat
> 5: retina.ENSG00000135776.wgt.RDat
> 6: retina.ENSG00000135776.wgt.RDat
>
> so on attempt to parallelize this I did this:
>
> library(parallel)
> library(data.table)
> library(foreach)
> library(doSNOW)
>
> n <- parallel::detectCores()
> cl <- parallel::makeCluster(n, type = "SOCK")
> doSNOW::registerDoSNOW(cl)
> files <- list.files("/WEIGHTS1/Retina", pattern=".RDat", ignore.case=T)
>
> lst_out <- foreach::foreach(i = seq_along(files),
> .packages = c("data.table") ) %dopar% {
>
> a <- get(load(files[i]))
> names <- rownames(a)
> data <- data.table(names, a["blup"])
> nm1 <- c("rsid", "ref_allele", "eff_allele")
> data[, (nm1) := tstrsplit(names, ":")[-2]]
> return(data[, .(rsid, weight = blup, ref_allele, eff_allele)][,
> WGT := files[i]][])
> }
> parallel::stopCluster(cl)
>
> big_data <- rbindlist(lst_out)
>
> I am getting this Error:
>
> Error in { : task 7 failed - "object 'blup' not found"
> > parallel::stopCluster(cl)
>
> Can you please advise,
> Ana
>
> ______________________________________________
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