GenABEL (version 1.8-0)

emp.qtscore: Genome-wide significance for a GWA scan

Description

Genome-wide significance for a GWA scan. Analysis function is qtscore.

Usage

emp.qtscore(formula , data, snpsubset, idsubset, strata, trait.type="gaussian", 
		times = 200, quiet=FALSE, bcast = 10)

Arguments

formula

Formula describing fixed effects to be used in analysis, e.g. y ~ a + b means that outcome (y) depends on two covariates, a and b. If no covariates used in analysis, skip the right-hand side of the equation.

data

An object of gwaa.data-class

snpsubset

Index, character or logical vector with subset of SNPs to run analysis on. If missing, all SNPs from data are used for analysis.

idsubset

Index, character or logical vector with subset of IDs to run analysis on. If missing, all people from data/cc are used for analysis.

strata

Stratification variable. If provieded, scores are computed within strata and then added up.

trait.type

"gaussian" or "binomial". If not specified, the procedure quesses the type

times

If more then one, the number of replicas to be used in derivation of empirical genome-wide significance. See emp.qtscore, which calls qtscore with times>1 for details

quiet

do not print warning messages

bcast

If the argument times > 1, progress is reported once in bcast replicas

Value

Object of class scan.gwaa-class

Details

In the analysis of empirical significance, first time the function qtscore is called and result object is saved. Later, the function qtscore is called times times with replace=FALSE in order to generate distribution under the null. Each call, minimal P-value is extracted and compared with original P-values. For a particular SNP, empirical P-value is obtained as a proportion of times minimal Ps from resampled data was less then original P.

The list elements effB, effAB and effBB are the ones obtained from the analysis of the original (not permuted) data set

The function does not yet implement correct analysis for X-linked data.

See Also

qtscore, emp.ccfast, scan.gwaa-class

Examples

require(GenABEL.data)
data(srdta)
a<-qtscore(qt3~age+sex,data=srdta,snps=c(1:200))
plot(a)
# this does not make sense, as the whole experiment must be analysed, not a small region!
# also, times = 20 is way too small (should be at least 200)
b<-emp.qtscore(qt3~age+sex,data=srdta,snps=c(1:200), times = 20)
plot(b)