Plot an interactive PCA plot

Plot an interactive PCA plot

Usage

plotPCA.ly(rld, intgroup)

Arguments

rld

DESeqTransform object output by varianceStabilizingTransformation() or rlog()

intgroup

character vector of names in colData(x) to use for grouping

Value

Handle to ggplot with added label field in aes_string() for plotting with ggplotly()

Examples

# make example dds object
dds <- DESeq2::makeExampleDESeqDataSet()

# normalize
rld <- DESeq2::varianceStabilizingTransformation(dds, blind=TRUE)

# make pca plot
p <- plotPCA.ly(rld, intgroup='condition')
#> using ntop=500 top features by variance