Scatterplot of BH adjusted P-values vs raw P-values from a null data

scatterhist_null

scatterhist <- function(x, y, xlab="", ylab=""){
# modify from https://www.r-bloggers.com/example-8-41-scatterplot-with-marginal-histograms/
    zones=matrix(c(2,0,1,3), ncol=2, byrow=TRUE)
    layout(zones, widths=c(4/5,1/5), heights=c(1/5,4/5))
    xhist = hist(x, plot=FALSE)
    yhist = hist(y, plot=FALSE)
    top = max(c(xhist$counts, yhist$counts))
    par(mar=c(3,3,1,1))
    plot(x,y)
    par(mar=c(0,3,1,1))
    barplot(xhist$counts, axes=FALSE, ylim=c(0, top), space=0)
    par(mar=c(3,0,1,1))
    barplot(yhist$counts, axes=FALSE, xlim=c(0, top), space=0, horiz=TRUE)
    par(oma=c(3,3,0,0))
    mtext(xlab, side=1, line=1, outer=TRUE, adj=0, 
          at=.4)
    mtext(ylab, side=2, line=1, outer=TRUE, adj=0, 
       at=.4)
}


library(limma)
set.seed(1234)
n <- 100
testexpr <- matrix(rnorm(n * 10, 5, 1), nc= 10)

design3 <- model.matrix(~ 0 + as.factor(c(rep(1,5), rep(2, 5))))
colnames(design3) <- c("A", "B")

fit3 <- lmFit(testexpr,design3)
contrasts.matrix3 <- makeContrasts("AvsB"=A-B, levels = design3)
fit3 <- eBayes(contrasts.fit(fit3, contrasts=contrasts.matrix3))

t3 <- topTable(fit3,coef=1, number = Inf)
with(t3, scatterhist(P.Value, adj.P.Val, xlab = "P-value", ylab = "BH adjusted P"))