plotPCs: Plot Samples in Subspace of Assigned PCs for a Given...
In dmoskowitz/mavric: Measuring Association between Variance and Covariates

Description Usage Arguments Details Value See Also

This function offers a visualization of the separation between levels of a categorical covariate, or across the range of a continuous covariate, within the context of the PC-subspace assigned to the covariate by estVC.

1 2	plotPCs(results, annotation, feature, pcset = NULL, cex = 1, lpos = "topleft", transp = TRUE, numberline = T, type = "p")

`results`	An object output by `estVC`
`annotation`	The ‘annotation’ data frame fed to `estVC` when creating ‘results’
`feature`	Column number in ‘annotation’ giving the covariate from which levels and the subspace should be obtained
`pcset`	Rather than using the associated PCs, plot along the specified PCs
`cex`	As in `par`, controls the size of points and labels
`lpos`	As in `legend`, controls the location of the legend
`transp`	Whether the legend box should be transparent (versus filled)

This function uses the coordinates from the PC-subspace assigned to a particular covariate, and plots the samples, colored according to the value the sample has for that covariate. For categorical covariates, samples are given different color by level; for continuous covariates, samples are plotted in grayscale.

Note, critically, that ‘feature’ refers to the *column number* in ‘annotation’ that is of interest, not to that column's name.

None

estVC for example usage, plotVars for Euler diagram plotting, scatterplot3d in the scatterplot3d package, par, and legend.