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Last data update: 2014.03.03

R: Plots the alignment of sequence tags on the genome given an...

plotGenome

R Documentation

Plots the alignment of sequence tags on the genome given an ‘aligmentData’ object and (optionally) a set of segments found.

Description

Plots the data from an alignmentData object for a given set of samples. Can optionally include in the plot the annotation data from a lociData object containing segment information.

Usage

plotGenome(aD, loci, chr = 1, limits = c(0, 1e4), samples = NULL,
plotType = "pileup", plotDuplicated = FALSE, density = 0, showNumber =
TRUE, logScale = FALSE, cap = Inf, ...)

Arguments

`aD`	An `alignmentData` object.
`loci`	A `lociData` object (produced by the `heuristicSeg` or `classifySeg` function and therefore) containing appropriate annotation information. Can be omitted if this annotation is not known/required.
`chr`	The name of the chromosome to be plotted. Should correspond to a chromosome name in the `alignmentData` object.
`limits`	The start and end point of the region to be plotted.
`samples`	The sample numbers of the samples to be plotted. If NULL, plots all samples.
`plotType`	The manner in which the plot is created. Currently only `plotType = pileup` is recommended.
`plotDuplicated`	If TRUE, then any duplicated sequence tags (i.e., sequence tags that match to multiple places in the genome) in the ‘aD’ object will be plotted on a negative scale for each sample. Defaults to FALSE (recommended).
`density`	The density of the shading lines to be used in plotting each segment.
`showNumber`	Should the row number of each segment be shown?
`logScale`	Should a log scale be used for the number of sequence tags found at each base?
`cap`	A numeric value defining a cap on the maximum number of reads to be plotted at any one point. Useful if a large number of reads at one location prevent a clear signal being seen elsewhere.
`...`	Any additional graphical parameters for passing to `plot`.

Value

Plotting function.

Author(s)

Thomas J. Hardcastle

Examples



# Define the chromosome lengths for the genome of interest.

chrlens <- c(2e6, 1e6)

# Define the files containing sample information.

datadir <- system.file("extdata", package = "segmentSeq")
libfiles <- c("SL9.txt", "SL10.txt", "SL26.txt", "SL32.txt")

# Establish the library names and replicate structure.

libnames <- c("SL9", "SL10", "SL26", "SL32")
replicates <- c(1,1,2,2)

# Process the files to produce an `alignmentData' object.

alignData <- readGeneric(file = libfiles, dir = datadir, replicates =
replicates, libnames = libnames, chrs = c(">Chr1", ">Chr2"), chrlens =
chrlens, gap = 100)

# Plot the alignments to the genome on chromosome 1 between bases 1 and 10000

plotGenome(alignData, chr = ">Chr1", limits = c(1, 1e5))

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(segmentSeq)
Loading required package: baySeq
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: abind
Loading required package: perm
Loading required package: ShortRead
Loading required package: BiocParallel
Loading required package: Biostrings
Loading required package: XVector
Loading required package: Rsamtools
Loading required package: GenomicAlignments
Loading required package: SummarizedExperiment
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/segmentSeq/plotGenome.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plotGenome
> ### Title: Plots the alignment of sequence tags on the genome given an
> ###   'aligmentData' object and (optionally) a set of segments found.
> ### Aliases: plotGenome
> ### Keywords: hplot
> 
> ### ** Examples
> 
> 
> 
> # Define the chromosome lengths for the genome of interest.
> 
> chrlens <- c(2e6, 1e6)
> 
> # Define the files containing sample information.
> 
> datadir <- system.file("extdata", package = "segmentSeq")
> libfiles <- c("SL9.txt", "SL10.txt", "SL26.txt", "SL32.txt")
> 
> # Establish the library names and replicate structure.
> 
> libnames <- c("SL9", "SL10", "SL26", "SL32")
> replicates <- c(1,1,2,2)
> 
> # Process the files to produce an `alignmentData' object.
> 
> alignData <- readGeneric(file = libfiles, dir = datadir, replicates =
+ replicates, libnames = libnames, chrs = c(">Chr1", ">Chr2"), chrlens =
+ chrlens, gap = 100)
Reading files........done!
Analysing tags...........done!
> 
> # Plot the alignments to the genome on chromosome 1 between bases 1 and 10000
> 
> plotGenome(alignData, chr = ">Chr1", limits = c(1, 1e5))
Computing plot.....done!
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>