meanVarPlot

meanVarPlot-methods

meanVarPlot,SeqExpressionSet-method


<code>meanVarPlot</code> produces a <code>smoothScatter</code> plot of the mean variance relation.


methods

Numerical and graphical summaries of RNA-Seq read data.
Within-lane normalization procedures to adjust for GC-content
effect (or other gene-level effects) on read counts: loess
robust local regression, global-scaling, and full-quantile
normalization (Risso et al., 2011). Between-lane normalization
procedures to adjust for distributional differences between
lanes (e.g., sequencing depth): global-scaling and
full-quantile normalization (Bullard et al., 2010).

Davide Risso

EDASeq

Exploratory Data Analysis and Normalization for RNA-Seq

meanVarPlot-methods function

<dl> <dt><code>signature(x = "SeqExpressionSet")</code></dt><dd>
It takes as additional argument <code>log</code>, which if true consider the logarithm of the counts before computing mean and variance. To avoid missing values, we consider the maximum between 0 and the log of the counts. Along with the scatter plot the function plots a line representing the <code><a rd-options="" href="/link/lowess?package=EDASeq&version=2.6.2" data-mini-rdoc="EDASeq::lowess">lowess</a></code> fit.
</dd> </dl>

Methods

<code>meanVarPlot</code> produces a <code>smoothScatter</code> plot of the mean variance relation.

meanVarPlot-methods: Methods for Function `meanVarPlot` in Package EDASeq

Description

Arguments

Methods