qtscore {GenABEL}R Documentation

Fast score test for association

Description

Fast score test for association between a trait and genetic polymorphism

Usage

qtscore(formula,data,snpsubset,idsubset,strata,trait.type="gaussian",times=1,quiet=FALSE,bcast=10,clambda=TRUE,propPs=1.0,details=TRUE)

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"
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
clambda If inflation facot Lambda is estimated as lower then one, this parameter controls if the original P1df (clambda=TRUE) to be reported in Pc1df, or the original 1df statistics is to be multiplied onto this "deflation" factor (clambda=FALSE). If a numeric value is provided, it is used as a correction factor.
propPs proportion of non-corrected P-values used to estimate the inflation factor Lambda, passed directly to the estlambda
details when FALSE, only SNP and ID names are not reported in the returned object (saves some memory). This is experimental and will be not mantained anymore as soon as we achieve better memory efficiency for storage of SNP and ID names (currently default R character data type used)

Details

When formula contains covariates, the traits is analysed using GLM and later residuals used when score test is computed for each of the SNPs in analysis. For binary traits, residuals from GLM are transformed using exp(x)/(1+exp(x)).

With no adjustment for binary traits, 1 d.f., the test is equivalent to the Armitage test.

This is a valid function to analyse GWA data, including X chromosome. For X chromosome, stratified analysis is performed (strata=sex).

Value

Object of class scan.gwaa-class

Author(s)

Yurii Aulchenko

See Also

mmscore, egscore, emp.qtscore, plot.scan.gwaa, scan.gwaa-class

Examples

data(srdta)
#qtscore with stratification
a <- qtscore(qt3~sex,data=srdta)
plot(a)
b <- qtscore(qt3,strata=srdta@phdata$sex,data=srdta)
add.plot(b,col="green",cex=2)
# qtscore with extra adjustment
a <- qtscore(qt3~sex+age,data=srdta)
a
plot(a)
# compare results of score and chi-square test for binary trait
a1 <- ccfast("bt",data=srdta,snps=c(1:100))
a2 <- qtscore(bt,data=srdta,snps=c(1:100),trait.type="binomial")
plot(a1,ylim=c(0,2))
add.plot(a2,col="red",cex=1.5)
# the good thing about score test is that we can do adjustment...
a2 <- qtscore(bt~age+sex,data=srdta,snps=c(1:100),trait.type="binomial")
points(a2$map,-log10(a2$P1df),col="green")

[Package GenABEL version 1.3-1 Index]