Contrasts matrix for group-means

Since you're using the group-means parametrization, there is now an extra step in the limma pipeline. The coefficients now represent the mean expression level for each of the two groups of samples, so you need to specify a custom contrast to test for differences between the progressive and stable leukemias.

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Differential Expression Analysis with limma in R

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Petunjuk latihan

The ExpressionSet object eset with the leukemia data and the design matrix you just created (design) have been loaded in your workspace.

Use makeContrasts to define the contrast status, which is the difference in the mean expression level between the progressive and stable cancers.
Pass the design matrix design to the argument levels. This allows the column names of design (which correspond to the coefficients) to be used in the definitions of the contrasts.

Latihan interaktif praktis

Cobalah latihan ini dengan menyelesaikan kode contoh berikut.

# Load package
library(limma)

# Create a contrasts matrix
cm <- ___(status = ___ - ___,
                    levels = ___)

# View the contrasts matrix
cm

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