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,times=1,quiet=FALSE,bcast=10,clambda=TRUE)

Arguments

formula Formula to be used in analysis. It should be a character string (thus quotation marks from both sides) following the standard notation. On the left-had side, there should be outcome. On the right-hand side, covariates are liste, with "+" separating the covariates (additive action). The left- and right-hand sides are separated by "~". You should put CRSNP argument in the formula. For example "qt3~CRSNP" assumes a crude analysis of association between SNPs and trait "qt3". To adjust for e.g. age and sex, use "qt3~age+sex+CRSNP". At current stage, only additive effects ("+") are allowed.
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
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" facor (clambda=FALSE)

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

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

Examples

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

[Package GenABEL version 1.1-8 Index]