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Post by moldach on Jan 25, 2019 17:56:31 GMT
I keep getting a message saying "killed" when trying to do the segment based LD score step on my data which makes me think it's a memory issue. gcta64 --bfile test --ld-score-region 200 --out test In the basic GREML tutorial it suggests you can split up the data by chromosome, like so: gcta64 --bfile test --chr 1 --maf 0.01 --make-grm --out test_chr1 --thread-num 10 gcta64 --bfile test --chr 2 --maf 0.01 --make-grm --out test_chr2 --thread-num 10 ... gcta64 --bfile test --chr 22 --maf 0.01 --make-grm --out test_chr22 --thread-num 10 Is it possible to do something similar for GREML in WGS or imputed data? For example:
gcta64 --bfile test --chr 1 --ld-score-region 200 --out test_chr1 gcta64 --bfile test --chr 2 --ld-score-region 200 --out test_chr2 ... lds_seg = read.table("test_ch1.score.ld",header=T,colClasses=c("character",rep("numeric",8))) lds_seg = read.table("test_ch2.score.ld",header=T,colClasses=c("character",rep("numeric",8))) ...
So that I would have stratified SNPs by segment-based LD score for each chromosome and then make GRMs for each of these groups:
chr1_snp_group1.txt chr1_snp_group2.txt chr1_snp_group3.txt chr1_snp_group4.txt ... chr22_snp_group1.txt chr22_snp_group2.txt chr22_snp_group3.txt And then perform the REML analysis on those 88 GRMs? Just wondering if that's a valid approach or if there's some way to deal with out-of-memory issues with large GWAS/imputed data?
Another question is how do you submit gcta64 properly on PBS with qsub to parallelize? In the PBS script I specify "#PBS -l nodes=1:ppn=10" and for the gcta command I'm putting --thread-num 10; however, according to htop it looks like it's only using one thread?
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anbai
New Member
Posts: 4
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Post by anbai on Sept 1, 2021 12:40:29 GMT
If you perform REML analysis on those 88 GRMs, your memory will explode. Not 100% sure, I don't think it's valid this approach.
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Post by tacrolimus on Mar 13, 2023 13:16:55 GMT
I have been getting similar issues and was wondering if you found a workaround?
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