shareTest {SHARE}R Documentation

Permutation Test for the Results from SHARE Algorithm

Description

Permutation tests to compute the experimentwise p-values that account for model searching.

Usage

shareTest(outObj, haploObj, status, tol = 1e-08, verbose = FALSE,
          nperm = 1000)

Arguments

outObj the share object outputed from cshare function
haploObj The haplo object cshare applied to
status A character string indicating the column name of the phenotype in haploObj@pheno to be used as the clinical status in the analysis.
tol The convergence parameter for the haplotype logistic regression.
verbose TRUE/FALSE to decide whether to create log file for debug
nperm maximal number of permutation tests

Details

If the best model size is zero, there appears to be no genetic association in the region of interest. There is no need to perform a permutation test. For final models with at least 1 SNPs, we permute case-control labels 1000 times regardless of the genotypic data, carry out model searching for each permuted dataset, and compute the nominal p-value using a Wald test. Finally the experiment-wise p-value is computed by comparing the observed p-value to its null distribution.

Value

The experiment-wise p-value from the permutation test will be returned.

Author(s)

James Y. Dai

References

J. Y. Dai, M. LeBlanc, N. L. Smith, B. M. Psaty, and C. Kooperberg. SHARE: an adaptive algorithm to select the most informative set of SNPs for genetic association. Biostatistics, 2009. In press.

J. Besag and P. Clifford. Sequential monte carlo p-values. Biometrika, 78(2):301, June 1, 1991.

See Also

cshare

Examples

## Not run: 
## See vignette for more details
permuPValue <- shareTest(outObj=kerem[["Cross-Val"]],
                         haploObj=keremHaplo,
                         status = "CF",
                         nperm=1000 
                         )
## End(Not run)

[Package SHARE version 1.0.4 Index]