A function to plot the scores resulting from fitting a PPCA model to metabolomic data.
ppca.scores.plot(output, group = FALSE)An object resulting from fitting a PPCA model.
Should it be relevant, a vector indicating the known treatment group membership of each observation.
This function produces a series of scatterplots each illustrating the estimated score for each observation within the reduced q dimensional space. The uncertainty associated with the score estimate is also illustrated through its 95
It is often the case that observations are known to belong to treatment groups; the treatment group membership of each observation can be illustrated on the plots produced by utilizing the `group' argument.
Nyamundanda, G., Gormley, I.C. and Brennan, L. (2010) Probabilistic principal components analysis for metabolomic data. Technical report. University College Dublin, Ireland.