Last data update: 2014.03.03

R: Plot trajectories of quantiles across arrays
quantilePlotR Documentation

Plot trajectories of quantiles across arrays

Description

Plot trajectories of quantiles across arrays.

Usage

quantilePlot(
    dat, 
    fileName, 
    probs = c(0, 0.05, 0.25, 0.5, 0.75, 0.95, 1), 
    plotOutPutFlag = FALSE, 
    requireLog2 = FALSE, 
    sortFlag = TRUE,
    cex = 1, 
    ylim = NULL, 
    xlab = "", 
    ylab = "intensity", 
    lwd = 3, 
    main = "Trajectory plot of quantiles", 
    mar = c(15, 4, 4, 2) + 0.1, 
    las = 2, 
    cex.axis = 1, 
    ...)

Arguments

dat

Expression data. Rows are gene probes; columns are arrays.

fileName

File name of output figure.

probs

quantiles (any real values between the interval [0, 1]).

plotOutPutFlag

logical. plotOutPutFlag=TRUE indicates the plots will be output to pdf format files. Otherwise, the plots will not be output to external files.

requireLog2

logical. requiredLog2=TRUE indicates probe expression levels will be log2 transformed. Otherwise, no transformation will be performed.

sortFlag

logical. sortFlag=TRUE indicates arrays will be sorted by the ascending order of MAD (median absolute deviation)

cex

numerical value giving the amount by which plotting text and symbols should be magnified relative to the default. see par.

ylim

Range of y axis.

xlab

Label of x axis.

ylab

Label of y axis.

lwd

The line width, a _positive_ number, defaulting to '1'. see par.

main

Charater string. main title of the plot.

mar

A numerical vector of the form 'c(bottom, left, top, right)' which gives the number of lines of margin to be specified on the four sides of the plot. The default is 'c(5, 4, 4, 2) + 0.1'. see par.

las

'las' numeric in 0,1,2,3; the style of axis labels. 0 - always parallel to the axis, 1 - always horizontal, 2 - always perpendicular to the axis, or 3 - always vertical.

see par.

cex.axis

The magnification to be used for axis annotation relative to the current setting of cex.

see par.

...

Arguments to be passed to plot.

Value

The quantile matrix with row quantiles and column array.

Author(s)

Weiliang Qiu <stwxq@channing.harvard.edu>, Brandon Guo <brandowonder@gmail.com>, Christopher Anderson <christopheranderson84@gmail.com>, Barbara Klanderman <BKLANDERMAN@partners.org>, Vincent Carey <stvjc@channing.harvard.edu>, Benjamin Raby <rebar@channing.harvard.edu>

Examples

    # generate simulated data set from conditional normal distribution
    set.seed(1234567)
    es.sim = genSimData.BayesNormal(nCpGs = 100, 
      nCases = 20, nControls = 20,
      mu.n = -2, mu.c = 2,
      d0 = 20, s02 = 0.64, s02.c = 1.5, testPara = "var",
      outlierFlag = FALSE, 
      eps = 1.0e-3, applier = lapply) 
    print(es.sim)


   png(file="qplot.png")
quantilePlot(
  dat = exprs(es.sim), 
  probs = c(0, 0.05, 0.25, 0.5, 0.75, 0.95, 1), 
  plotOutPutFlag = FALSE, 
  requireLog2 = FALSE, 
  sortFlag = TRUE)
dev.off()
  

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(iCheck)
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: lumi
Setting options('download.file.method.GEOquery'='auto')
Setting options('GEOquery.inmemory.gpl'=FALSE)
Loading required package: gplots

Attaching package: 'gplots'

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

    lowess

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/iCheck/quantilePlot.Rd_%03d_medium.png", width=480, height=480)
> ### Name: quantilePlot
> ### Title: Plot trajectories of quantiles across arrays
> ### Aliases: quantilePlot
> ### Keywords: methods
> 
> ### ** Examples
> 
>     # generate simulated data set from conditional normal distribution
>     set.seed(1234567)
>     es.sim = genSimData.BayesNormal(nCpGs = 100, 
+       nCases = 20, nControls = 20,
+       mu.n = -2, mu.c = 2,
+       d0 = 20, s02 = 0.64, s02.c = 1.5, testPara = "var",
+       outlierFlag = FALSE, 
+       eps = 1.0e-3, applier = lapply) 
>     print(es.sim)
ExpressionSet (storageMode: lockedEnvironment)
assayData: 100 features, 40 samples 
  element names: exprs 
protocolData: none
phenoData
  sampleNames: subj1 subj2 ... subj40 (40 total)
  varLabels: arrayID memSubj
  varMetadata: labelDescription
featureData
  featureNames: probe1 probe2 ... probe100 (100 total)
  fvarLabels: probe gene chr memGenes
  fvarMetadata: labelDescription
experimentData: use 'experimentData(object)'
Annotation:  
> 
> 
> #   png(file="qplot.png")
> quantilePlot(
+   dat = exprs(es.sim), 
+   probs = c(0, 0.05, 0.25, 0.5, 0.75, 0.95, 1), 
+   plotOutPutFlag = FALSE, 
+   requireLog2 = FALSE, 
+   sortFlag = TRUE)
***** Arrays were sorted by MAD (median absolute deviation)!
> #dev.off()
>   
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>