A function to plot the scores resulting from fitting a PPCCA model to metabolomic data.

1 | ```
ppcca.scores.plot(output, Covars, group = FALSE, covarnames=NULL)
``` |

`output` |
An object resulting from fitting a PPCCA model. |

`Covars` |
An N x L covariate data matrix where each row is a set of covariates. |

`group` |
Should it be relevant, a vector indicating the known treatment group membership of each observation. |

`covarnames` |
Should it be relevant, a vector string indicating the names of the covariates. |

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 Gift, Isobel Claire Gormley and Lorraine Brennan

Nyamundanda, G., Gormley, I.C. and Brennan, L. (2010) Probabilistic principal components analysis for metabolomic data. Technical report. University College Dublin, Ireland.

`ppcca.metabol`

, `ppcca.metabol.jack`

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.