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Hi, I am using the sim1000G R package to simulate data for case/control study. I can not figure out how to manipulate this code to be able to generate 10% or 50% causal SNPs in R. This is whole code provided as example on GitHub: library(sim1000G) vcf_file = "region-chr4-357-ANK2.vcf.gz" #nvariants = 442, ss=1000 vcf = readVCF( vcf_file, maxNumberOfVariants = 442 ,min_maf = 0.0005,max_maf = 0.01) #lowest MAF dim( vcf$gt1 ) #rows represent number of variants, columns represent number of individuals ## Download and use full chromosome gene...

...; > Hi, > > I am using the sim1000G R package to simulate data for case/control study. > I can not figure out how to manipulate this code to be able to generate 10% > or 50% causal SNPs in R. > > This is whole code provided as example on GitHub: > > library(sim1000G) > vcf_file = "region-chr4-357-ANK2.vcf.gz" #nvariants = 442, ss=1000 > > vcf = readVCF( vcf_file, maxNumberOfVariants = 442 ,min_maf = > 0.0005,max_maf = 0.01) #lowest MAF > dim( vcf$gt1 ) #rows represent number of variants, columns represent > number of individuals > > ## Down...