Find Correlation Between Principal Components (PCs) and Covariates

DEGreport::degCovariates() wrapper supporting a bcbioRNASeq object.

plotPCACovariates(object, ...)

# S4 method for bcbioRNASeq
plotPCACovariates(object, metrics = TRUE,
  transform = "rlog", ...)

Arguments

object

Object.
...

Additional arguments, passed to DEGreport::degCovariates().
metrics

Include sample summary metrics as covariates. Defaults to include all metrics columns (TRUE), but desired columns can be specified here as a character vector.
transform

String specifying DESeqTransform slotted inside the bcbioRNASeq object:

  • rlog (recommended).

  • vst: variance stabilizing transformation.

Value

ggplot.

See also

Examples

plotPCACovariates(bcb, metrics = TRUE)
#> 
#> running pca and calculating correlations for:
#> un-scaled  data in pca; pve >= 5%; spearman correlations 
plotPCACovariates(bcb, metrics = c("exonicRate", "intronicRate"))
#> 
#> running pca and calculating correlations for:
#> un-scaled  data in pca; pve >= 5%; spearman correlations