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.

Diese Übung ist Teil des Kurses

Differential Expression Analysis with limma in R

Anleitung zur Übung

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 subset fit2 like you did in the treatment-contrasts parametrization because there is no intercept term in the group-means model.

Interaktive Übung

Versuche dich an dieser Übung, indem du diesen Beispielcode vervollständigst.

# 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)

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