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.
Questo esercizio fa parte del corso
Differential Expression Analysis with limma in R
Istruzioni dell'esercizio
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 subsetfit2like you did in the treatment-contrasts parametrization because there is no intercept term in the group-means model.
Esercizio pratico interattivo
Prova a risolvere questo esercizio completando il codice di esempio.
# 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)