Visualize batch effects
In the olfactory stem cell experiment, there were 7 treatments with 4 replicates each for a total of 28 samples. However, these 28 samples were processed in 4 separate batches. The effect of the treatments is of biological interest, but the effect of the batches is technical noise. Using dimension reduction, determine which of these two effects had a larger impact on the gene expression data.
This exercise is part of the course
Differential Expression Analysis with limma in R
Exercise instructions
The ExpressionSet object eset
with the olfactory stem cell data has been loaded in your workspace.
Use
plotMDS
to plot the principal components. Label the samples by the treatment they received, and setgene.selection
to"common"
.Re-visualize the principal components, labeling the samples by their batch.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Load package
library(limma)
# Plot principal components labeled by treatment
___(eset, labels = pData(eset)[, "___"], gene.selection = "___")
# Plot principal components labeled by batch
___(eset, labels = pData(eset)[, "___"], gene.selection = "___")