gcdhPower: GCDH power analysis
In CollapsABEL: Generalized CDH (GCDH) Analysis

Description Usage Arguments Details Author(s)

This function makes use of runTypeI. Random phenotypes are used to survey p-values under the null hypothesis (SNPs are not associated phenotype), and genome-wide significance thresholds for single-SNP approach and GCDH are calculated by a user given alpha-level. A custom phe_fun is supplied for simulating a phenotype associated with a certain pair of SNPs. Total number of such simulations is set by the n_simu parameter. In each simulation 4 p-values are generated:

1 2	gcdhPower(rbed_info, n_shift, n_simu, maf_min, maf_max, r_limit, beta, collapse_matrix = NULL, dist_threshold = 5e+05, alpha_level = 0.05)

`rbed_info`	RbedInfoC object
`n_shift`	integer. `n_shift` for each GCDH run.
`n_simu`	integer. Number of simulations to run.
`maf_min`	numeric. Lower limit of MAF interval.
`maf_max`	numeric. Upper limit of MAF interval.
`r_limit`	numeric. Upper limit of correlation coefficient between the two causal SNPs.
`beta`	numeric. Effect size of the simulated phenotype.
`collapse_matrix`	See runGcdh.
`dist_threshold`	See runGcdh.
`alpha_level`	numeric. Control type-I error rate at this level.

P_single: p-values from single-SNP approach.

P_GCDH: p-values from GCDH.

P_(single,no causal): p-values from single-SNP approach when causal SNPs are untyped.

P_(GCDH,no causal): p-values from GCDH when causal SNPs are untyped.

When all simulations are finished, 4 vectors of p-values are obtained: P_single_vec, P_GCDH_vec, P_(single,no causal)_vec, P_(GCDH,no causal)_vec. The power for each of the category (single-SNP, single-SNP without causal genotypes, GCDH, GCDH without causal genotypes) are proportions of these vectors that are more significant than the genome-wide significance thresholds we have obtained.

Kaiyin Zhong

CollapsABEL documentation built on May 1, 2019, 7:28 p.m.