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  3. Differential Expression Analysis with limma in R
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Pre-process features

In the video exercise, you saw that the sample distributions for the doxorubicin study were extremely right-skewed. Thus, the first step you need to take is to pre-process the features: log-transform, normalize, and filter.

指示

100 XP

The ExpressionSet object eset_raw with the raw data has been loaded in your workspace. The limma package is loaded.

  • Log transform the measurements. Use plotDensities to visualize. Label the samples by their genotype.

  • Quantile normalize the measurements with normalizeBetweenArrays and re-visualize.

  • Use rowMeans to determine which genes have a mean expression level greater than 0.

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