Description Usage Format Source Examples
The data set simGWAS was simulated using PLINK where the SNPs
were binned into different allele frequency ranges. There are 250 controls
and 250 cases, i.e. a binary response and 500 subjects.
The variables age and sex
are two additional control variables. The variables SNP.1 till
SNP.990 were simulated to have no association with the response and
the variables SNP.991 till SNP.1000 have a population odds
ratio of 2.
1 |
A list with three elements:
xa matrix with 500 rows and 1000 columns where the rows
and columns correspond to the subjects and variables, respectively.
The variables are named SNP.1, ..., SNP.1000.
ybinary response vector with 500 elements where the elements correspond to the subjects.
clvara matrix with 500 rows and 2 columns where the rows
and columns correspond to the subjects and variables, respectively.
The age of the subject is stored in the variable age. The
variable sex takes the value 0 for men and 1 for women.
Buzdugan L (2018). hierGWAS: Asessing statistical significance in predictive GWA studies. R package version 1.10.0.
1 2 3 4 5 6 7 8 9 10 | data(simGWAS)
sim.geno <- simGWAS$x
sim.pheno <- simGWAS$y
sim.clvar <- simGWAS$clvar
dendr <- cluster_var(x = sim.geno)
set.seed(1234)
result <- test_hierarchy(x = sim.geno, y = sim.pheno,
dendr = dendr, clvar = sim.clvar,
family = "binomial")
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