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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.

Bu egzersiz

Differential Expression Analysis with limma in R

kursunun bir parçasıdır
Kursu Görüntüle

Egzersiz talimatları

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.

Uygulamalı interaktif egzersiz

Bu örnek kodu tamamlayarak bu egzersizi bitirin.

# 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)
Kodu Düzenle ve Çalıştır