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  3. Differential Expression Analysis with limma in R

Exercise

Filter genes

Now that the data have been log-transformed and quantile-normalized, you need to remove the lowly expressed genes that are not relevant to the system being studied.

Instructions

100 XP

The ExpressionSet object eset_norm with the normalized Populus data has been loaded in your workspace.

  • Use plotDensities to visualize the distribution of gene expression levels for each sample. Disable the legend.

  • Use rowMeans to determine which genes have a mean expression level greater than 5. Name this logical vector keep.

  • Filter the genes (i.e. rows) of the ExpressionSet object with the logical vector keep and re-visualize.