./plink2 --bgen [.bgen Filename] --sample [.sample filename] --recode vcf --snps 3:46457412_T_C --out [Filename]
Start time: Thu Jun 27 15:50:19 2019 257923 MiB RAM detected; reserving 128961 MiB for main workspace. Using up to 64 threads (change this with --threads). --bgen: 6696680 variants detected, format v1.2. 487409 samples imported from .sample file to rs113010081Imputation-temporary.psam . --bgen: 6696k variants scanned. --bgen: 58k variants converted.
However, if you need to perform many queries of this sort, and you only need dosages and not the raw genotype probability triplets, plink2 is extremely efficient if you convert to pgen format just once, and then work with that.
If you only need to do this once, plink2 is not the best tool for the job. Use something like bgenix instead.
However, if you need to perform many queries of this sort, and you only need dosages and not the raw genotype probability triplets, plink2 is extremely efficient if you convert to pgen format just once, and then work with that.
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Dear Christopher,Is there a place that I could read up on the cutoffs plink use to convert the non-integer genotype data from .bgen into the integer genotypes in .pgen, and how does it decide missing data?I realize that a portion of the data was determined as missing data by plink.Thanks a lot.April
On Thu, Jun 27, 2019 at 7:22 PM Christopher Chang wrote:
If you only need to do this once, plink2 is not the best tool for the job. Use something like bgenix instead.
However, if you need to perform many queries of this sort, and you only need dosages and not the raw genotype probability triplets, plink2 is extremely efficient if you convert to pgen format just once, and then work with that.
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