Design matrix for 2x2 factorial

In this 2x2 factorial experiment to investigate the effect of drought on tree growth, 2 different types of Populus tree were grown with 2 different amounts of water. In order to have one model coefficient per group, you need to first combine the two variables.

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Differential Expression Analysis with limma in R

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The ExpressionSet object eset with the Populus data has been loaded in your workspace.

Combine the variables type (the type of tree) and water (normal vs. drought) into a single factor variable.
Use model.matrix to create a design matrix with no intercept.

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# Create single variable
group <- with(___(eset), paste(___, ___, sep = "."))
group <- factor(group)

# Create design matrix with no intercept
design <- model.matrix(~___ + ___)
colnames(design) <- levels(group)

# Count the number of samples modeled by each coefficient
colSums(design)

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