Differential Expression Analysis with limma in R
John Blischak
Instructor
wt
), Top2b null (top2b
)pbs
), doxorubicin (dox
)dim(eset)
Features Samples
29532 12
table(pData(eset)[, c("genotype", "treatment")])
treatment
genotype dox pbs
top2b 3 3
wt 3 3
plotDensities(eset,
group = pData(eset)[, "genotype"],
legend = "topright")
Log transform
Quantile normalize
Filter
boxplot(<y-axis> ~ <x-axis>, main = "<title>")
boxplot(<gene expression> ~ <phenotype>, main = "<feature>")
boxplot(<Top2b expression> ~ <genotype>, main = "<Top2b info>")
Principal components analysis
limma function plotMDS
How many clusters do you anticipate?
Differential Expression Analysis with limma in R