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Specify a linear model to compare 2 groups

To identify differentially expressed genes for the leukemia experiment, you need to translate the following linear model to R:

where \(X_{1}\) is equal to 1 for progressive cancers and 0 for stable cancers (note: R automatically chooses the base condition by alphabetical order).

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 leukemia data has been loaded in your workspace.

  • Use model.matrix to construct a design matrix with an intercept coefficient and a coefficient that indicates the disease status.

Hands-on interactive exercise

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

# Create design matrix for leukemia study
design <- ___(~___, data = ___(eset))

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