noise-class


The class <code>noise</code> is returned when applying <code><a rd-options="" href="/link/investNoise?package=lmms&version=1.3.3" data-mini-rdoc="lmms::investNoise">investNoise</a></code> method.


Linear Mixed effect Model Splines ('lmms') implements linear mixed
effect model splines for modelling and differential expression for highly
dimensional data sets: investNoise() for quality control and filterNoise() for
removing non-informative trajectories; lmmSpline() to model time course expression
profiles and lmmsDE() performs differential expression analysis to identify
differential expression between groups, time and/or group x time interaction.

Jasmin Straube

lmms

Linear Mixed Effect Model Splines for Modelling and Analysis of
Time Course Data

noise-class function

 <dl>
<dt><code>name</code></dt><dd><code>character</code> vector. The name of the trajectory.</dd> <dt><code>RT</code></dt><dd>A <code>numeric</code> vector, containing the time to molecule standard deviation ratios for every trajectory.</dd> <dt><code>RI</code></dt><dd>A <code>numeric</code> vector, containing the individual to molecule standard deviation ratios for every trajectory.</dd> <dt><code>propMissing</code></dt><dd>A <code>numeric</code> vector, containing the proportion of missing values for every trajectory.</dd> <dt><code>foldChange</code></dt><dd>A <code>numeric</code> vector, containing the maximum fold change of the mean between any two time points.</dd> </dl>

noise-class: `noise` S4 class

Description

Arguments

Slots