plot.job {BayesPeak} | R Documentation |
Plot the distribution of reads in a .bed file, with BayesPeak's calls highlighted.
plot.job(x, raw.out, job, strand = "+", threshold = 0.5, xlim = c(0,1), highlight = TRUE, col.un = "grey", col.enr = "blue", bin = 100L, ...)
x |
RangedData (from the IRanges package) with a value column entitled |
raw.out |
Raw output from the |
job |
Integer. The number of the job to plot. |
strand |
Character. Strand to plot - usually either "+" or "-". If the |
threshold |
Numeric. Bins with a PP higher than this value will be classed as enriched. |
xlim |
Numeric vector. This controls which part of the job is plotted. For example, |
highlight |
Logical. FIXME |
col.un |
The colour used to plot counts in unenriched bins. |
col.enr |
The colour used to plot counts in enriched bins. |
bin |
What sized bin should be used? Currently, this value should be the same as the value used in |
... |
Additional arguments to be passed through to |
Similar to plot.bed
, plot.job
takes the reads in a bed file, and plots a histogram of their locations - i.e. plots the bin counts. It then goes on to highlight the histogram bins that have been made in the raw.output from bayespeak
.
It is worth bearing in mind that BayesPeak takes the information on both strands into account when calling peaks, and therefore judgements based on a one-stranded view of the data should be treated with caution. For a better picture of what is going on, both strands should be viewed simultaneously, as is done in the examples below.
Plots a histogram on the active graphical device.
Jonathan Cairns
Spyrou C, Stark R, Lynch AG, Tavare S BayesPeak: Bayesian analysis of ChIP-seq data, BMC Bioinformatics 2009, 10:299 doi:10.1186/1471-2105-10-299
bayespeak
, read.bed
, plot.bed
.
##get the ChIP .bed file dir <- system.file("extdata", package="BayesPeak") treatment <- file.path(dir, "H3K4me3reduced.bed") bed <- read.bed(treatment) ##get the corresponding raw.output object data(raw.output.H3K4me3) ##plot job 1, + and - strand par(mfrow = c(2,1)) plot.job(bed, raw.output.H3K4me3, 1) plot.job(bed, raw.output.H3K4me3, 1, "-") ##zoom in for a closer look... plot.job(bed, raw.output.H3K4me3, 1, xlim = c(0.58,0.6)) plot.job(bed, raw.output.H3K4me3, 1, "-", xlim = c(0.58,0.6))