Create a boxplot with an ExpressionSet object

Now that you've combined all the experimental data into one ExpressionSet object, it is more convenient to subset the features and samples. In this exercise, you'll once again create a boxplot to visualize one gene, but this time also subset the samples that are included in the plot.

This exercise is part of the course

Differential Expression Analysis with limma in R

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Exercise instructions

The ExpressionSet eset has been loaded in your workspace.

Subset eset to only the first 10 samples (columns).
Create a boxplot of the 1000th gene (i.e. row) in eset_sub using the accessor functions exprs, pData, and fData.

Hands-on interactive exercise

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

# Subset to only include the first 10 samples (columns)
eset_sub <- eset[___]

# Check the dimensions of the subset
dim(eset_sub)

# Create a boxplot of the 1000th gene in eset_sub
boxplot(___(eset_sub)[___, ] ~ ___(eset_sub)[, "Disease"],
        main = ___(eset_sub)[___, "symbol"])

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