Plot scores from a fitted PPCCA model.

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Description

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

Usage

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

Arguments

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.

Details

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.

Author(s)

Nyamundanda Gift, Isobel Claire Gormley and Lorraine Brennan

References

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

See Also

ppcca.metabol, ppcca.metabol.jack

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