qq plot 是为了检验实际分布与假设分布是否相同。
    我的数据来自于plink处理后生成的p值，所以不同的分布根据实际情况修改。
    下面函数来自于 qqman 包，可定制性太差，就改下用ggplot2画。

    1. qq = function(pvector, ...) {
    3.     # Check for sensible input
    4.     if (!is.numeric(pvector)) stop("Input must be numeric.")
    6.     # limit to not missing, not nan, not null, not infinite, between 0 and 1
    7.     pvector <- pvector[!is.na(pvector) & !is.nan(pvector) & !is.null(pvector) & is.finite(pvector) & pvector<1 & pvector>0]
    9.     # Observed and expected
    10.     o = -log10(sort(pvector,decreasing=FALSE))
    11.     e = -log10( ppoints(length(pvector) ))
    14. #     # The old way
    15. #     plot(e, o, pch=20, 
    16. #          xlab=expression(Expected~~-log[10](italic(p))), 
    17. #          ylab=expression(Observed~~-log[10](italic(p))), 
    18. #          ...)
    20.     # The new way to initialize the plot.
    21.     ## See http://stackoverflow.com/q/23922130/654296
    22.     ## First, define your default arguments
    23.     def_args <- list(pch=20, xlim=c(0, max(e)), ylim=c(0, max(o)), 
    24.                      xlab=expression(Expected~~-log[10](italic(p))), 
    25.                      ylab=expression(Observed~~-log[10](italic(p)))
    26.     )
    27.     ## Next, get a list of ... arguments
    28.     #dotargs <- as.list(match.call())[-1L]
    29.     dotargs <- list(...)
    30.     ## And call the plot function passing NA, your ... arguments, and the default
    31.     ## arguments that were not defined in the ... arguments.
    32.     tryCatch(do.call("plot", c(list(x=e, y=o), def_args[!names(def_args) %in% names(dotargs)], dotargs)), warn=stop)
    34.     # Add diagonal
    35.     abline(0,1,col="red")
    37. }

    使用 ggplot2 作图

    1. qq_dat <- data.frame(obs=-log10(sort(pd_dat$P,decreasing=FALSE)),
    2.                      exp=-log10( ppoints(length(pd_dat$P))))
    3. pd_qq <- ggplot(data=qq_dat,aes(exp,obs))+
    4.   geom_point(alpha=0.7,color="#7F7F7FFF")+
    5.   geom_abline(color="#D62728FF")+
    6.   xlab("Expected -log10(P-value)")+
    7.   ylab("Observed -log10(P-value)")+
    8.   scale_x_continuous(limits = c(0,7))+
    9.   scale_y_continuous(limits = c(0,7))+
    10.   theme(
    11.     axis.title = element_text(size=12,face="bold"),
    12.     axis.text = element_text(face="bold",size=8,color = "black"),
    13.     #axis.line = element_line(size=0.8,color="black"),
    14.     axis.ticks= element_line(size=0.8,colour = "black"),
    15.     panel.grid =element_blank(),
    16.     panel.border = element_rect(fill=NA,size = 0.8),
    17.     panel.background = element_blank())

    plot_zoom_png.png