## ---- include=FALSE-----------------------------------------------------------
library(qqman)
library(knitr)
opts_chunk$set(comment=NA, fig.width=12, fig.height=9, message=FALSE, tidy=TRUE, dpi=75)

## ----generatedata, eval=FALSE, echo=FALSE-------------------------------------
#  # This code used to generate the test data. Runs slow, but does the job.
#  chrstats <- data.frame(chr=1:22, nsnps=1500)
#  chrstats$nsnps <- with(chrstats, round(nsnps/chr^(1/3)))
#  chrstats
#  
#  d <- data.frame(SNP=rep(NA, sum(chrstats$nsnps)),
#                  CHR=rep(NA, sum(chrstats$nsnps)),
#                  BP=rep(NA, sum(chrstats$nsnps)),
#                  P=rep(NA, sum(chrstats$nsnps)))
#  snpi <- 1
#  set.seed(42)
#  for (i in chrstats$chr) {
#      for (j in 1:chrstats[i, 2]) {
#          d[snpi, ]$SNP=paste0("rs", snpi)
#          d[snpi, ]$CHR=i
#          d[snpi, ]$BP=j
#          d[snpi, ]$P=runif(1)
#          snpi <- snpi+1
#      }
#  }
#  
#  divisor <- c(seq(2,50,2), seq(50,2,-2))
#  divisor <- divisor^4
#  length(divisor)
#  d[3026:3075, ]$P <- d[3026:3075, ]$P/divisor
#  snpsOfInterest <- paste0("rs", 3001:3100)
#  qq(d$P)
#  manhattan(d, highlight=snpsOfInterest)
#  gwasResults <- d
#  save(gwasResults, file="data/gwasResults.RData")

## -----------------------------------------------------------------------------
str(gwasResults)
head(gwasResults)
tail(gwasResults)

## -----------------------------------------------------------------------------
as.data.frame(table(gwasResults$CHR))

## -----------------------------------------------------------------------------
manhattan(gwasResults)

## -----------------------------------------------------------------------------
manhattan(gwasResults, main="Manhattan Plot", ylim=c(0,10), cex=0.6, cex.axis=0.9, col=c("blue4", "orange3"), suggestiveline=F, genomewideline=F, chrlabs=c(1:20, "P", "Q"))

## -----------------------------------------------------------------------------
manhattan(subset(gwasResults, CHR==1))

## -----------------------------------------------------------------------------
str(snpsOfInterest)
manhattan(gwasResults, highlight=snpsOfInterest)

## -----------------------------------------------------------------------------
manhattan(subset(gwasResults, CHR==3), highlight=snpsOfInterest, xlim=c(200, 500), main="Chr 3")

## -----------------------------------------------------------------------------
manhattan(gwasResults, annotatePval=0.01)

## -----------------------------------------------------------------------------
manhattan(gwasResults, annotatePval=0.005, annotateTop=FALSE)

## -----------------------------------------------------------------------------
# Add test statistics
gwasResults <- transform(gwasResults, zscore=qnorm(P/2, lower.tail=FALSE))
head(gwasResults)

# Make the new plot
manhattan(gwasResults, p="zscore", logp=FALSE, ylab="Z-score", genomewideline=FALSE, suggestiveline=FALSE, main="Manhattan plot of Z-scores")

## -----------------------------------------------------------------------------
qq(gwasResults$P)

## -----------------------------------------------------------------------------
qq(gwasResults$P, main="Q-Q plot of GWAS p-values",
   xlim=c(0,7), ylim=c(0,12), pch=18, col="blue4", cex=1.5, las=1)