Quantify and interpret multiple sources of biological and technical variation in gene expression experiments. Uses a linear mixed model to quantify variation in gene expression attributable to individual, tissue, time point, or technical variables.  Includes dream differential expression analysis for repeated measures.

Quantify and interpret divers of variation in multilevel gene
expression experiments

package-ubuntu-20.04-r-4.0.5#cran#variancePartition-1.20.0

<p>Enable subsetting on MArrayLM2 object. Same as for MArrayLM, but apply column subsetting to df.residual and cov.coefficients.list
</p>

<table summary="R argblock">
<tr valign="top">
<td><code>object</code></td>
<td>
<p>MArrayLM2</p>
</td>
</tr>
<tr valign="top">
<td><code>i</code></td>
<td>
<p>row</p>
</td>
</tr>
<tr valign="top">
<td><code>j</code></td>
<td>
<p>col</p>
</td>
</tr>
</table>

package-ubuntu-20.04-r-4.0.5#cran#variancePartition-1.20.0#docs#subset.MArrayLM2-method

subset.MArrayLM2-method

Description

Arguments

Value

variancePartition

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`object`	MArrayLM2
`i`	row
`j`	col