aTest: Hypothesis testing for annotation enrichment

In dongjunchung/GPA: GPA (Genetic analysis incorporating Pleiotropy and Annotation)

Description

Hypothesis testing for annotation enrichment.

Usage

aTest( fitWithoutAnn, fitWithAnn, vDigit=1000 )

Arguments

fitWithoutAnn	GPA model fit without using annotation data.
fitWithAnn	GPA model fit with using annotation data.
vDigit	Number of digits for reporting parameter estimates and standard errors. For example, setting it to 1000 means printing out values up to three digits below zero.

Details

aTest implements the hypothesis testing for annotation enrichment. It requires two GPA model fits, one fitted with using annotation data and one fitted without using annotation data, and evaluates annotation enrichment for risk-associated SNPs using the likelihood ratio test.

Value

Returns a list with components:

q	q estimates.
statistics	Statistics of the test for annotation enrichment.
pvalue	p-value of the test for annotation enrichment.

Author(s)

Dongjun Chung

References

Chung D*, Yang C*, Li C, Gelernter J, and Zhao H (2014), "GPA: A statistical approach to prioritizing GWAS results by integrating pleiotropy information and annotation data," PLoS Genetics, 10: e1004787. (* joint first authors)

See Also

pTest, GPA, GPA.

Examples

## Not run: 
# GPA without annotation data

fit.GPA.noAnn <- GPA( pmat, NULL )
		
# GPA with annotation data

fit.GPA.wAnn <- GPA( pmat, ann )

# hypothesis testing for annotation enrichment

test.annotation <- aTest( fit.GPA.noAnn, fit.GPA.wAnn )

## End(Not run)

dongjunchung/GPA documentation built on March 1, 2020, 3:44 a.m.