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Last data update: 2014.03.03

R: Plot many side by side scores XOR loadings plots

plotPcs

R Documentation

Plot many side by side scores XOR loadings plots

Description

A function that can be used to visualise many PCs plotted against each other

Usage

plotPcs(object, pcs = 1:nP(object), type = c("scores", "loadings"),
  sl = NULL, hotelling = 0.95, ...)

Arguments

`object`	`pcaRes` a pcaRes object
`pcs`	`numeric` which pcs to plot
`type`	`character` Either "scores" or "loadings" for scores or loadings plot respectively
`sl`	`character` Text labels to plot instead of a point, if NULL points are plotted instead of text
`hotelling`	`numeric` Significance level for the confidence ellipse. NULL means that no ellipse is drawn.
`...`	Further arguments to `pairs` on which this function is based.

Details

Uses pairs to provide side-by-side plots. Note that this function only plots scores or loadings but not both in the same plot.

Value

None, used for side effect.

Author(s)

Henning Redestig

Examples

data(iris)
pcIr <- pca(iris[,1:4], nPcs=3,  method="svd")
plotPcs(pcIr, col=as.integer(iris[,4]) + 1)

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(pcaMethods)
Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.


Attaching package: 'pcaMethods'

The following object is masked from 'package:stats':

    loadings

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/pcaMethods/plotPcs.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plotPcs
> ### Title: Plot many side by side scores XOR loadings plots
> ### Aliases: plotPcs
> ### Keywords: multivariate
> 
> ### ** Examples
> 
> data(iris)
> pcIr <- pca(iris[,1:4], nPcs=3,  method="svd")
> plotPcs(pcIr, col=as.integer(iris[,4]) + 1)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>