VulcanoPlot

Plot log2 fold changes against -log10 multiple testing adjusted P values

Nucleotide conversion sequencing experiments have been
developed to add a temporal dimension to RNA-seq and single-cell RNA-seq. Such
experiments require specialized tools for primary processing such as GRAND-SLAM,
(see 'Jürges et al' <doi:10.1093/bioinformatics/bty256>) and specialized tools for
downstream analyses. 'grandR' provides a comprehensive toolbox for quality control,
kinetic modeling, differential gene expression analysis and visualization of such data.

Florian Erhard

grandR

Comprehensive Analysis of Nucleotide Conversion Sequencing Data

Teresa Rummel

Lygeri Sakellaridi

Kevin Berg

VulcanoPlot function

<dl><dt>data</dt>
<dd>the grandR object that contains the data to be plotted</dd>
<dt>analysis</dt>
<dd>the analysis to plot (default: first analysis)</dd>
<dt>p.cutoff</dt>
<dd>p-value cutoff (default: 0.05)</dd>
<dt>lfc.cutoff</dt>
<dd>log fold change cutoff (default: 1)</dd>
<dt>annotate.numbers</dt>
<dd>if TRUE, label the number of genes</dd>
<dt>...</dt>
<dd>further parameters passed to PlotScatter</dd></dl>

Arguments

Make a Vulcano plot — VulcanoPlot

<dl>

<dt>data</dt>
<dd>the grandR object that contains the data to be plotted</dd>


<dt>analysis</dt>
<dd>the analysis to plot (default: first analysis)</dd>


<dt>p.cutoff</dt>
<dd>p-value cutoff (default: 0.05)</dd>


<dt>lfc.cutoff</dt>
<dd>log fold change cutoff (default: 1)</dd>


<dt>annotate.numbers</dt>
<dd>if TRUE, label the number of genes</dd>


<dt>...</dt>
<dd>further parameters passed to PlotScatter</dd>

</dl>

VulcanoPlot: Make a Vulcano plot

Description

Usage

Value

Arguments