Estimate a threshold from Gaussian mixture distribution

Description

Function to estimate a threshold from Gaussian mixture distribution. The data is assumed to follow a mixture of two Gaussian distributions. The one Gaussian with the lower mean value is assumed to be the null distribution and probe levels are assigned p-values based on this null distribution. The threshold is then the minimal data value with an adjusted p-value smaller than a specified threshold.

Usage

twoGaussiansNull(x, p.adj.method = "BY", max.adj.p = 0.1, var.equal = FALSE, ...)

Arguments

Details

This function uses the package mclust to fit a mixture of two Gaussians to the data. The threshold is then estimated from the fitted Gaussian with the lower mean value.

Value

Single numeric value. The threshold that is the minimal data value with an adjusted p-value smaller than a specified threshold.

Note

Please note that the use of the package 'mclust' is only free for strict academic use (see the license of 'mclust' here: http://www.stat.washington.edu/mclust/license.txt ). The alternative function upperBoundNull does not have this restriction.

Thanks to Richard Bourgon for pointing out the necessity of providing this method as an alternative way of estimating the threshold.

Author(s)

Joern Toedling, Aleksandra Pekowska

See Also

mclust, p.adjust, upperBoundNull

Examples

  exDir <- system.file("exData",package="Ringo")
  load(file.path(exDir,"exampleProbeAnno.rda"))
  load(file.path(exDir,"exampleX.rda"))
  smoothX <- computeRunningMedians(exampleX, probeAnno=exProbeAnno,
     modColumn = "Cy5", allChr = "9", winHalfSize = 400)

  ## compare the two different ways of estimating the threshold
  y0a <- apply(exprs(smoothX), 2, upperBoundNull)
  y0b <- apply(exprs(smoothX), 2, twoGaussiansNull)

  hist(exprs(smoothX)[,1], n=10, main=NA,
       xlab="Smoothed expression level [log2]")
  abline(v=c(y0a, y0b), col=c("blue","orange"), lwd=2)
  legend(x="topright", col=c("blue","orange"), lwd=2, 
         legend=c(expression(paste(y[0]," Non-parametric")),
                  expression(paste(y[0]," Gaussian"))))

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(Ringo)
Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Loading required package: RColorBrewer
Loading required package: limma

Attaching package: 'limma'

The following object is masked from 'package:BiocGenerics':

    plotMA

Loading required package: Matrix
Loading required package: grid
Loading required package: lattice
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/Ringo/twoGaussiansNull.Rd_%03d_medium.png", width=480, height=480)
> ### Name: twoGaussiansNull
> ### Title: Estimate a threshold from Gaussian mixture distribution
> ### Aliases: twoGaussiansNull
> ### Keywords: manip
> 
> ### ** Examples
> 
>   exDir <- system.file("exData",package="Ringo")
>   load(file.path(exDir,"exampleProbeAnno.rda"))
>   load(file.path(exDir,"exampleX.rda"))
>   smoothX <- computeRunningMedians(exampleX, probeAnno=exProbeAnno,
+      modColumn = "Cy5", allChr = "9", winHalfSize = 400)

Chromosome 9 ...
Suz12_vs_total ... 
Construction result ExpressionSet...Done.
> 
>   ## compare the two different ways of estimating the threshold
>   y0a <- apply(exprs(smoothX), 2, upperBoundNull)
>   y0b <- apply(exprs(smoothX), 2, twoGaussiansNull)
Loading required package: mclust
Package 'mclust' version 5.2
Type 'citation("mclust")' for citing this R package in publications.
> 
>   hist(exprs(smoothX)[,1], n=10, main=NA,
+        xlab="Smoothed expression level [log2]")
>   abline(v=c(y0a, y0b), col=c("blue","orange"), lwd=2)
>   legend(x="topright", col=c("blue","orange"), lwd=2, 
+          legend=c(expression(paste(y[0]," Non-parametric")),
+                   expression(paste(y[0]," Gaussian"))))
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>