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:

`x`

a 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`

.`y`

binary response vector with 500 elements where the elements correspond to the subjects.

`clvar`

a 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")
``` |

crbasel/hierinf documentation built on Nov. 5, 2018, 5:22 p.m.

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