Numeric data matrix. Rows are probes; columns are arrays.
curveNames
Probe names.
fileName
file name of output figure.
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.
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
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
no return value.
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)
# plot trajectories of the first 5 genes
plotCurves(
dat = exprs(es.sim)[1:5,],
curveNames = featureNames(es.sim)[1:5],
plotOutPutFlag=FALSE,
cex = 0.5,
requireLog2 = FALSE)
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/plotCurves.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plotCurves
> ### Title: Plot trajectories of probe profiles across arrays
> ### Aliases: plotCurves
> ### 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:
>
> # plot trajectories of the first 5 genes
> plotCurves(
+ dat = exprs(es.sim)[1:5,],
+ curveNames = featureNames(es.sim)[1:5],
+ plotOutPutFlag=FALSE,
+ cex = 0.5,
+ requireLog2 = FALSE)
>
>
>
>
>
>
> dev.off()
null device
1
>
providing 
.