Closed garyzhubc closed 2 years ago
There are only 40359612 snp_id and 632 samples. I thought 125G is enough for this.
Yes, this should be more than enough.
What is the error you get exactly?
Dear Peiyuan,
Am I correctly understanding that you're using ~40 million variants? For better computational performance and more accurate PRS, I would recommend you restrict to hapmap3 SNPs or other high quality SNP set that also excludes rare SNPs. Since you don't have many samples I would also use a stringent MAF threshold of about 1% or greater.
Best, Bjarni
There are only 40359612 snp_id and 632 samples. I thought 125G is enough for this.
This is the error I got
> chr <- snp_readBGEN("chr.bgen","chr",list(snp_id))
Error: out of memory
I'm running this on a cluster with 125G memory and 32 CPUs
It worked after following Bjarni's suggestion, but I doubt it's really a memory issue, because I for sure have enough memory even including the rare variants
Maybe the problem comes from storing the $map
information.
How large is the object right now? (object.size()
)
Could you please extrapolate this number for the full number of variants?
I cannot load the object in, because it says out of memory, so I can't really read the full variant. The current object is only of size 1G.
Gonna close this because I'll just use the one pruned by maf
Not enough memory for loading bgen file. My bgen file has size 4G, and I have allocated 125G memory to do the processing. How much memory do I need? I though this library is gonna cache the big file?