plotMeth

loci


    The name of the chromosome to be plotted. Should correspond to a
    chromosome name in the <code>alignmentMeth</code> object. 
  


    The start and end point of the region to be plotted.
  

limits


    The sample numbers of the samples to be plotted. If NULL, plots all samples.


samples


    Should the row number of each segment be shown?
  

showNumber


    The rgb code (<code><a rd-options="" href="/link/rgb?package=segmentSeq&version=2.6.0" data-mini-rdoc="segmentSeq::rgb">rgb</a></code>) with which to colour the loci.



    The angle at which loci are shaded (see <code><a rd-options="" href="/link/rect?package=segmentSeq&version=2.6.0" data-mini-rdoc="segmentSeq::rect">rect</a></code>).


angle


    Caps the maximum level of coverage shown on the plot; thus, if a
    base has been sequenced at a level greater than the cap, the data
    for that base will be shown as if it has a coverage of cap.



    If TRUE, adds the plot of methylation level to the current
    plot. Defaults to FALSE.



This function takes an <code><a rd-options="" href="/link/alignmentMeth?package=segmentSeq&version=2.6.0" data-mini-rdoc="segmentSeq::alignmentMeth">alignmentMeth</a></code> object and plots the
observed levels of methylation within some defined region on the
genome. If a <code><a rd-options="" href="/link/methData?package=segmentSeq&version=2.6.0" data-mini-rdoc="segmentSeq::methData">methData</a></code> object is also supplied, loci of
methylation will also be shown.


hplot

High-throughput sequencing technologies allow the production of large volumes of short sequences, which can be aligned to the genome to create a set of matches to the genome. By looking for regions of the genome which to which there are high densities of matches, we can infer a segmentation of the genome into regions of biological significance. The methods in this package allow the simultaneous segmentation of data from multiple samples, taking into account replicate data, in order to create a consensus segmentation. This has obvious applications in a number of classes of sequencing experiments, particularly in the discovery of small RNA loci and novel mRNA transcriptome discovery.

Thomas J Hardcastle

segmentSeq

Methods for identifying small RNA loci from high-throughput
sequencing data

plotMeth function

An <code><linkS4class>alignmentMeth</linkS4class></code>.

The name of the chromosome to be plotted. Should correspond to a
    chromosome name in the <code>alignmentMeth</code> object.

The start and end point of the region to be plotted.

The sample numbers of the samples to be plotted. If NULL, plots all samples.

Should the row number of each segment be shown?

The rgb code (<code><a href="rgb" rd-options="">rgb</a></code>) with which to colour the loci.

The angle at which loci are shaded (see <code><a href="rect" rd-options="">rect</a></code>).

Caps the maximum level of coverage shown on the plot; thus, if a
    base has been sequenced at a level greater than the cap, the data
    for that base will be shown as if it has a coverage of cap.

If TRUE, adds the plot of methylation level to the current
    plot. Defaults to FALSE.

This function takes an <code><a href="alignmentMeth" rd-options="">alignmentMeth</a></code> object and plots the
observed levels of methylation within some defined region on the
genome. If a <code><a href="methData" rd-options="">methData</a></code> object is also supplied, loci of
methylation will also be shown.

plotMeth: Plots a map of cytosine methylation (and optionally, methylation loci).

Description

Usage

Arguments

Value

See Also