## ----echo=FALSE--------------------------------------------------------------------------------------------- library(HIBAG) fn <- system.file("doc", "case_control.txt", package="HIBAG") ## ----------------------------------------------------------------------------------------------------------- dat <- read.table(fn, header=TRUE, stringsAsFactors=FALSE) head(dat) # make an object for hlaAssocTest hla <- hlaAllele(dat$sample.id, H1=dat$A, H2=dat$A.1, locus="A", assembly="hg19", prob=dat$prob) summary(hla) ## ----------------------------------------------------------------------------------------------------------- hlaAssocTest(hla, disease ~ h, data=dat) # 95% confidence interval (h.2.5%, h.97.5%) # show details print(hlaAssocTest(hla, disease ~ h, data=dat, verbose=FALSE)) hlaAssocTest(hla, disease ~ h, data=dat, prob.threshold=0.5) # regression with a threshold hlaAssocTest(hla, disease ~ h, data=dat, showOR=TRUE) # report odd ratio instead of log odd ratio hlaAssocTest(hla, disease ~ h + pc1, data=dat) # confounding variable pc1 hlaAssocTest(hla, disease ~ h, data=dat, model="additive") # use an additive model hlaAssocTest(hla, trait ~ h, data=dat) # continuous outcome ## ----------------------------------------------------------------------------------------------------------- aa <- hlaConvSequence(hla, code="P.code.merge") ## ----------------------------------------------------------------------------------------------------------- head(c(aa$value$allele1, aa$value$allele2)) # show cross tabulation at each amino acid position summary(aa) # association tests hlaAssocTest(aa, disease ~ h, data=dat, model="dominant") # try dominant models hlaAssocTest(aa, disease ~ h, data=dat, model="dominant", prob.threshold=0.5) # try dominant models hlaAssocTest(aa, disease ~ h, data=dat, model="recessive") # try recessive models ## ----------------------------------------------------------------------------------------------------------- sessionInfo()