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Last data update: 2014.03.03

R: Generate a MA-Plot

plotMA

R Documentation

Generate a MA-Plot

Description

Generates an MA-plot, which graphs the fold change versus the mean normalized expression. Statistically significant features are colored red.

Usage

plotMA(jscs, 
       FDR.threshold = 0.01, 
       fc.name = NULL,
       fc.thresh = 1,
       use.pch = 20,
       smooth.nbin = 256, 
       ylim = c( 1 / 1000,1000),
       use.smoothScatter = TRUE,
       label.counts = TRUE,
       label.axes = c(TRUE,TRUE,FALSE,FALSE), 
       show.labels = TRUE,
       par.cex = 1, points.cex = 1, text.cex = 1,
       lines.cex = 8,
       anno.lwd = 2, mar = c(4.1,4.1,3.1,1.1),
       miniTicks = TRUE, 
       verbose = TRUE, debug.mode = FALSE,
       ...)

Arguments

`jscs`	A `JunctionSeqCountSet`. Usually created by `runJunctionSeqAnalyses`. Alternatively, this can be created manually by `readJunctionSeqCounts`. However in this case a number of additional steps will be necessary: Dispersions and size factors must then be set, usually using functions `estimateSizeFactors` and `estimateJunctionSeqDispersions`. Hypothesis tests must be performed by `testForDiffUsage`. Effect sizes and parameter estimates must be created via `estimateEffectSizes`.
`FDR.threshold`	The FDR threshold used to color dots. Tests with an adjusted-p-value more significant than this threshold will be marked in red.
`fc.name`	The name of the column to take from fData(jscs).
`fc.thresh`	The fold-change threshold required to count a significant locus in the count labels. It will also draw horizontal lines at this threshold.
`use.pch`	The value of pch to pass to the `points` call.
`use.smoothScatter`	Logical. If TRUE, non-significant genes will be ploted with density shading.
`smooth.nbin`	The number of bins to smooth, for the density plot, if `use.smoothScatter` is TRUE.
`ylim`	The y-axis limits.
`label.counts`	Logical. If TRUE, include labels showing the number of loci that pass both the statistical-significance and fold-change threshold in each direction.
`label.axes`	Logical vector. Whether to label each axis. Must have length 4; each corresponds to the bottom, left, top, and right axes respectively.
`show.labels`	Logical. If TRUE, include all titles and axes labels.
`par.cex`	The cex value to be passed to `par`.
`points.cex`	The cex value to be passed to `points`.
`text.cex`	The cex value to be passed to `text`.
`lines.cex`	The cex value to be passed to `lines`, `box`, and similar.
`anno.lwd`	The lwd value to be passed to `lines`, `box`, `axis`, and similar.
`mar`	The margin sizes, expressed in lines. see `link{par}`.
`miniTicks`	Logical. If TRUE, then include "mini tick marks" on the x and y axes.
`verbose`	if TRUE, send debugging and progress messages to the console / stdout.
`debug.mode`	if TRUE, send even more debugging and progress messages to the console / stdout.
`...`	Additional graphical parameters.

Value

This is a side-effecting function, and does not return a value.

Examples

data(exampleDataSet,package="JctSeqData");
plotMA(jscs);


## Not run: 
########################################
#Set up example data:
decoder.file <- system.file(
                  "extdata/annoFiles/decoder.bySample.txt",
                  package="JctSeqData");
decoder <- read.table(decoder.file,
                  header=TRUE,
                  stringsAsFactors=FALSE);
gff.file <- system.file(
            "extdata/cts/withNovel.forJunctionSeq.gff.gz",
            package="JctSeqData");
countFiles <- system.file(paste0("extdata/cts/",
     decoder$sample.ID,
     "/QC.spliceJunctionAndExonCounts.withNovel.forJunctionSeq.txt.gz"),
     package="JctSeqData");
######################
#Run example analysis:
jscs <- runJunctionSeqAnalyses(sample.files = countFiles,
           sample.names = decoder$sample.ID,
           condition=factor(decoder$group.ID),
           flat.gff.file = gff.file,
           analysis.type = "junctionsAndExons"
);
########################################

#Plot M-A:
plotMA(jscs);


## End(Not run)

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(JunctionSeq)
Loading required package: SummarizedExperiment
Loading required package: GenomicRanges
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

Loading required package: S4Vectors
Loading required package: stats4

Attaching package: 'S4Vectors'

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

    colMeans, colSums, expand.grid, rowMeans, rowSums

Loading required package: IRanges
Loading required package: GenomeInfoDb
Loading required package: Biobase
Welcome to Bioconductor

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

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/JunctionSeq/plotMA.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plotMA
> ### Title: Generate a MA-Plot
> ### Aliases: plotMA
> 
> ### ** Examples
> 
> data(exampleDataSet,package="JctSeqData");
> plotMA(jscs);
> 
> 
> ## Not run: 
> ##D ########################################
> ##D #Set up example data:
> ##D decoder.file <- system.file(
> ##D                   "extdata/annoFiles/decoder.bySample.txt",
> ##D                   package="JctSeqData");
> ##D decoder <- read.table(decoder.file,
> ##D                   header=TRUE,
> ##D                   stringsAsFactors=FALSE);
> ##D gff.file <- system.file(
> ##D             "extdata/cts/withNovel.forJunctionSeq.gff.gz",
> ##D             package="JctSeqData");
> ##D countFiles <- system.file(paste0("extdata/cts/",
> ##D      decoder$sample.ID,
> ##D      "/QC.spliceJunctionAndExonCounts.withNovel.forJunctionSeq.txt.gz"),
> ##D      package="JctSeqData");
> ##D ######################
> ##D #Run example analysis:
> ##D jscs <- runJunctionSeqAnalyses(sample.files = countFiles,
> ##D            sample.names = decoder$sample.ID,
> ##D            condition=factor(decoder$group.ID),
> ##D            flat.gff.file = gff.file,
> ##D            analysis.type = "junctionsAndExons"
> ##D );
> ##D ########################################
> ##D 
> ##D #Plot M-A:
> ##D plotMA(jscs);
> ##D 
> ## End(Not run)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>