Test for differential expression for group-means
Now that you've specified the design matrix and the contrasts matrix, you can test for differential expression.
This exercise is part of the course
Differential Expression Analysis with limma in R
Exercise instructions
The ExpressionSet object eset
with the leukemia data, the design matrix (design
), and the contrasts matrix (cm
) have been loaded in your workspace.
Fit the model coefficients with
lmFit
.Fit the contrasts with
contrasts.fit
.Calculate the t-statistics with
eBayes
.Summarize the results with
decideTests
. You don't need to subsetfit2
like you did in the treatment-contrasts parametrization because there is no intercept term in the group-means model.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Load package
library(limma)
# Fit the model
fit <- ___(eset, ___)
# Fit the contrasts
fit2 <- ___(fit, contrasts = ___)
# Calculate the t-statistics for the contrasts
fit2 <- ___(fit2)
# Summarize results
results <- ___(fit2)
summary(results)