Number of reads or average coverage versus target length scatter plot

Description

Plots either numbers of on-target reads or average per-target coverage (or potentially other per-target values) against respective target lengths. A smoothing spline is added to the scatter plot.

Usage

coverage.targetlength.plot(targets, plotcolumn, linecol = 2, xlab, ylab, lwd, pch, cex, ...)

Arguments

Details

coverage.target and readsPerTarget can be used to calculate average per-target coverages and numbers of reads overlapping each target. The values are added to the RangedData table containing the target positions. Such RangedData table can then be used for plotting the calculated values against the respecitve target lengths.

Value

A scatterplot with the given per-target values on the y-axis and corresponding target lengths on the x-axis. A smoothing spline is added to the plot.

Author(s)

Manuela Hummel m.hummel@dkfz.de

See Also

coverage.target, readsPerTarget, covered.k, coverage.hist, coverage.uniformity, coverage.plot

Examples

## get reads and targets
exptPath <- system.file("extdata", package="TEQC")
readsfile <- file.path(exptPath, "ExampleSet_Reads.bed")
reads <- get.reads(readsfile, idcol=4, skip=0)
targetsfile <- file.path(exptPath, "ExampleSet_Targets.bed")
targets <- get.targets(targetsfile, skip=0)

## get average per-target coverage
Coverage <- coverage.target(reads, targets, perTarget=TRUE)
targets2 <- Coverage$targetCoverages

## get numbers of reads per target
targets2 <- readsPerTarget(reads, targets2)

## coverage vs target length
coverage.targetlength.plot(targets2, plotcolumn="avgCoverage", pch="o")

## coverage vs number of reads per target
coverage.targetlength.plot(targets2, plotcolumn="nReads", pch="o")

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)

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> library(TEQC)
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: IRanges
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: Rsamtools
Loading required package: GenomeInfoDb
Loading required package: GenomicRanges
Loading required package: Biostrings
Loading required package: XVector
Loading required package: hwriter
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/TEQC/coverage.targetlength.plot.Rd_%03d_medium.png", width=480, height=480)
> ### Name: coverage.targetlength.plot
> ### Title: Number of reads or average coverage versus target length scatter
> ###   plot
> ### Aliases: coverage.targetlength.plot
> ### Keywords: hplot
> 
> ### ** Examples
> 
> ## get reads and targets
> exptPath <- system.file("extdata", package="TEQC")
> readsfile <- file.path(exptPath, "ExampleSet_Reads.bed")
> reads <- get.reads(readsfile, idcol=4, skip=0)
[1] "read 19546 sequenced reads"
> targetsfile <- file.path(exptPath, "ExampleSet_Targets.bed")
> targets <- get.targets(targetsfile, skip=0)
[1] "read 50 (non-overlapping) target regions"
Warning message:
the "reduce" method for RangedData object is deprecated 
> 
> ## get average per-target coverage
> Coverage <- coverage.target(reads, targets, perTarget=TRUE)
> targets2 <- Coverage$targetCoverages
> 
> ## get numbers of reads per target
> targets2 <- readsPerTarget(reads, targets2)
> 
> ## coverage vs target length
> coverage.targetlength.plot(targets2, plotcolumn="avgCoverage", pch="o")
> 
> ## coverage vs number of reads per target
> coverage.targetlength.plot(targets2, plotcolumn="nReads", pch="o")
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>