DESeq2 results exploration

NOTE: It may take a bit longer to load this exercise.

To reduce the number of DE genes that we are returning and to reduce the likelihood of the DE genes being biologically meaningful, we are going to use a small log2 fold change threshold to determine the DE genes.

Questo esercizio fa parte del corso

RNA-Seq with Bioconductor in R

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Istruzioni dell'esercizio

Extract the smoc2 results using the results() function, similar to before, with an alpha of 0.05 and with normal as the base level of condition. However, this time use a log2 fold change threshold of 0.32. Assume all prior steps have been executed, including the creation of the DESeq2 object, dds_smoc2, and running the DESeq() function.
Perform shrinkage of the log2 foldchanges using the lfcShrink() function.

Esercizio pratico interattivo

Prova a risolvere questo esercizio completando il codice di esempio.

# Explore the results() function
?results

# Extract results
smoc2_res <- ___(___, 
                contrast = ___, 
                alpha = ___, 
                lfcThreshold = ___)

# Shrink the log2 fold changes
smoc2_res <- ___(___, 
                    ___, 
                    res = ___)

Modifica ed esegui il codice