R Under development (unstable) (2023-11-16 r85542 ucrt) -- "Unsuffered Consequences"
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> library(qtl)
> data(map10)
> map10 <- map10[1:2]
> set.seed(8789993)
> simcross <- sim.cross(map10, n.ind=125, type="bc",
+                       model=rbind(c(1, 50, 1.5), c(2, 50, 0)))
> simcross$pheno[,1] <- simcross$pheno[,1] + rnorm(nind(simcross), 0, 2*simcross$qtlgeno[,2])
> simcross <- calc.genoprob(simcross)
> out <- scanonevar(simcross,
+                   tol=0.01)
> summary(out, format="allpeaks")
  chr  pos neglogP_mean   pos neglogP_disp
1   1 58.6         1.65 107.5        0.841
2   2 62.2         1.17  51.8        5.817
> 
> ####
> 
> data(fake.bc)
> fake.bc <- fake.bc[1:2,1:150] # only chr 1 and 2, and first 100 individuals
> fake.bc <- calc.genoprob(fake.bc, step=5)
> out <- scanonevar(fake.bc,
+                   tol=0.01)
> summary(out, format="allpeaks")
  chr  pos neglogP_mean pos neglogP_disp
1   1  9.8        0.995  20        0.514
2   2 30.0        2.200  50        1.702
> covar <- fake.bc$pheno[,c("sex", "age")]
> out <- scanonevar(fake.bc, mean_covar=covar, var_covar=covar,
+                   tol=0.01)
> summary(out, format="allpeaks")
  chr pos neglogP_mean  pos neglogP_disp
1   1   5        0.725 37.1         2.31
2   2  30        5.202 30.0         2.28
> 
> #########Simulate a vQTL on Chromosome 1########
> 
> chromo=1
> qtl.position=14 # 50 cM
> N=nind(fake.bc)
> a1<-fake.bc$geno[[chromo]]$prob[,,1]
> y <- fake.bc$pheno$pheno1
> y <- y + rnorm(N,0,exp(a1[,qtl.position]))
> out <- scanonevar(fake.bc, y, mean_covar=covar, var_covar=covar)
> summary(out, format="allpeaks")
  chr pos neglogP_mean  pos neglogP_disp
1   1  45        0.784 70.0        5.781
2   2   0        0.368 21.8        0.672
> 
> out <- scanonevar(fake.bc, y, mean_covar=covar,
+                   tol=0.01)
> summary(out, format="allpeaks")
  chr pos neglogP_mean  pos neglogP_disp
1   1  45        0.746 70.0        6.012
2   2   0        0.380 72.1        0.617
> 
> out <- scanonevar(fake.bc, y, var_covar=covar,
+                   tol=0.01)
> summary(out, format="allpeaks")
  chr  pos neglogP_mean  pos neglogP_disp
1   1 45.0        0.896 70.0         3.41
2   2 72.1        0.645 21.8         0.53
> 
> out <- scanonevar(fake.bc, y,
+                   tol=0.01)
> summary(out, format="allpeaks")
  chr  pos neglogP_mean  pos neglogP_disp
1   1 45.0        0.838 70.0        3.486
2   2 72.1        0.654 21.8        0.486
> 
> proc.time()
   user  system elapsed 
   4.06    0.34    4.39