PcaPlots: PCA plots
In metabolomics: Analysis of Metabolomics Data

Description Usage Arguments Author(s) See Also Examples

Produces PCA plots.

1 2	PcaPlots(inputdata, y.axis = 1, x.axis = 2, center=TRUE, scale = TRUE, main = NULL, varplot = FALSE, multiplot = FALSE, n = 5, cols = NULL, ...)

`inputdata`	A log transformed data frame in the input data format. See `metabolomics` for details.
`y.axis`	The principal component to be plotted on the y-axis.
`x.axis`	The principal component to be plotted on the x-axis.
`center`	A logical indicating whether the variables should be scaled to have zero mean.
`scale`	A logical indicating whether the variables should be scaled to have unit variance before the analysis takes place.
`main`	Plot title.
`varplot`	A logical indicating whether explained variance should be plotted.
`multiplot`	If `TRUE`, pairs plots of the first n principal components will be plotted.
`n`	The number of principal components to be plotted if `multiplot=TRUE`. The default value is set to 5.
`cols`	A character string with colours to be used.
`...`	Arguments to be passed on to other methods.

Alysha M De Livera, Jairus B Bowne

prcomp.

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    data(treated)
    treated.log <- LogTransform(treated)$output
    PcaPlots(treated.log, scale=FALSE, center=TRUE, multiplot = TRUE, varplot = TRUE)