DIR="H:/Wenjian/SV-spacc/packages-new/v0.1/"   # directory to store package

install.packages(paste0(DIR,"SV2bc_0.1.tar.gz"), repos = NULL, type = "source")
library(SV2bc)

set.seed(1)
nsub=1e7;  # number of subjects   

########### The below is to simulate dataset
b0=1
b1=0       # effect size of genotype on secondary phenotype, 0 for null model. 
maf=0.3
OR.D.X <- 1;   # OR value between D (disease status) and X (genotype). If data is simulated based on lin's method, the simulated data follow OR value; if data is simulated based on set-valued model, OR value is slightly biased.
OR.D.Y <- 2;   # OR value between D (disease status) and Y (secondary phenotype). 
simu.model="lin"        # "lin" or "sv" for lin's method and set-valued model, respectively.
sp.type="continuous"    # "continuous" or "binary"
prev=0.05;
gamma.est <- para.est(OR.D.X,OR.D.Y,prev,b0,b1,maf,simu.model,sp.type)
g0=gamma.est[1];
g1=gamma.est[2];
g2=gamma.est[3];
data.res <- data.simu(nsub,g0,g1,g2,b0,b1,maf,simu.model,sp.type)
D <- data.res[,1];   # disease status for the population
n.smp <- 1000;       # sample size for either case group or control group.
data <- data.res[c(sample(which(D==1),n.smp),
                   sample(which(D==0),n.smp)),]
########### END of data simulation

########### Main function to compute p-value and other parameters

SV2bc.test(data,prev,sp.type)   # pval.sp should be 0.7117