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.

This exercise is part of the course

Differential Expression Analysis with limma in R

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Exercise instructions

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.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# 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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