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Last data update: 2014.03.03

R: Plot organelle assignment data and results.

plot2D

R Documentation

Plot organelle assignment data and results.

Description

Generate 2 dimensional or feature distribution plots to illustrate localistation clusters. In plot2D, rows containing NA values are removed prior to dimention reduction.

Usage

plot2D(object, fcol = "markers", fpch, unknown = "unknown", dims = 1:2,
  score = 1, method = "PCA", methargs, axsSwitch = FALSE,
  mirrorX = FALSE, mirrorY = FALSE, col, pch, cex, index = FALSE,
  idx.cex = 0.75, identify = FALSE, plot = TRUE, ...)

Arguments

`object`	An instance of class `MSnSet`.
`fcol`	Feature meta-data label (fData column name) defining the groups to be differentiated using different colours. Default is `markers`. Use `NULL` to suppress any colouring.
`fpch`	Featre meta-data label (fData column name) desining the groups to be differentiated using different point symbols.
`unknown`	A `character` (default is `"unknown"`) defining how proteins of unknown/un-labelled localisation are labelled.
`dims`	A `numeric` of length 2 defining the dimensions to be plotted. Always 1:2 for MDS.
`score`	A numeric specifying the minimum organelle assignment score to consider features to be assigned an organelle. (not yet implemented).
`method`	A `character` describe how to transform the data or what to plot. One of `"PCA"` (default), `"MDS"`, `"kpca"` or `"t-SNE"`, defines what dimensionality reduction is applied: principal component analysis (see `prcomp`), classical multidimensional scaling (see `cmdscale`), kernel PCA (see `kernlab::kpca`) or t-SNE (see `tsne::tsne`). `"scree"` can also be used to produce a scree plot. If none is used, the data is plotted as is, i.e. without any transformation. In this case, `object` can either be an `MSnSet` or a `matrix` (as invisibly returned by `plot2D`). This enables to re-generate the figure without computing the dimensionality reduction over and over again, which can be time consuming for certain methods. Available methods are listed in `plot2Dmethods`. If `object` is a `matrix`, an `MSnSet` containing the feature metadata must be provided in `methargs` (see below for details).
`methargs`	A `list` of arguments to be passed when `method` is called. If missing, the data will be scaled and centred prior to PCA. If `method = "none"` and `object` is a `matrix`, then the first and only argument of `methargs` must be an `MSnSet` with matching features with `object`.
`axsSwitch`	A `logical` indicating whether the axes should be switched.
`mirrorX`	A `logical` indicating whether the x axis should be mirrored?
`mirrorY`	A `logical` indicating whether the y axis should be mirrored?
`col`	A `character` of appropriate length defining colours.
`pch`	A `character` of appropriate length defining point character.
`cex`	Character expansion.
`index`	A `logical` (default is `FALSE`, indicating of the feature indices should be plotted on top of the symbols.
`idx.cex`	A `numeric` specifying the character expansion (default is 0.75) for the feature indices. Only relevant when `index` is TRUE.
`identify`	A logical (default is `TRUE`) defining if user interaction will be expected to identify individual data points on the plot. See also `identify`.
`plot`	A `logical` defining if the figure should be plotted. Useful when retrieving data only. Default is `TRUE`.
`...`	Additional parameters passed to `plot` and `points`.

Details

Note that plot2D has been update in version 1.3.6 to support more organelle classes than colours defined in getStockcol. In such cases, the default colours are recycled using the default plotting characters defined in getStockpch. See the example for an illustration. The alpha argument is also depreciated in version 1.3.6. Use setStockcol to set colours with transparency instead. See example below.
Version 1.11.3: to plot data as is, i.e. without any transformation, method can be set to "none" (as opposed to passing pre-computed values to method as a matrix, in previous versions). If object is an MSnSet, the untransformed values in the assay data will be plotted. If object is a matrix with coordinates, then a matching MSnSet must be passed to methargs.

Value

Used for its side effects of generating a plot. Invisibly returns the 2d data.

Author(s)

Laurent Gatto <lg390@cam.ac.uk>

Examples

library("pRolocdata")
data(dunkley2006)
plot2D(dunkley2006, fcol = NULL)
## available methods
plot2Dmethods
plot2D(dunkley2006, fcol = NULL, method = "kpca")
plot2D(dunkley2006, fcol = NULL, method = "kpca",
       methargs = list(kpar = list(sigma = 1)))
plot2D(dunkley2006, fcol = "markers")
addLegend(dunkley2006,
          fcol = "markers",
          where = "topright",
          cex = 0.5, bty = "n", ncol = 3)
title(main = "plot2D example")
## Using transparent colours
setStockcol(paste0(getStockcol(), "80"))
plot2D(dunkley2006, fcol = "markers")
## New behavious in 1.3.6 when not enough colours
setStockcol(c("blue", "red", "green"))
getStockcol() ## only 3 colours to be recycled
getMarkers(dunkley2006)
plot2D(dunkley2006)
## reset colours
setStockcol(NULL)
plot2D(dunkley2006, method = "none") ## plotting along 2 first fractions
plot2D(dunkley2006, dims = c(3, 5), method = "none") ## plotting along fractions 3 and 5
## pre-calculate PC1 and PC2 coordinates
pca <- plot2D(dunkley2006, plot=FALSE)
head(pca)
plot2D(pca, method = "none", methargs  = list(dunkley2006))

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.
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Type 'license()' or 'licence()' for distribution details.

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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(pRoloc)
Loading required package: MSnbase
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

Loading required package: Biobase
Welcome to Bioconductor

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

Loading required package: mzR
Loading required package: Rcpp
Loading required package: BiocParallel
Loading required package: ProtGenerics

This is MSnbase version 1.20.7 
  Read '?MSnbase' and references therein for information
  about the package and how to get started.


Attaching package: 'MSnbase'

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

    smooth

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

    trimws

Loading required package: MLInterfaces
Loading required package: annotate
Loading required package: AnnotationDbi
Loading required package: stats4
Loading required package: IRanges
Loading required package: S4Vectors

Attaching package: 'S4Vectors'

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

    colMeans, colSums, expand.grid, rowMeans, rowSums

Loading required package: XML
Loading required package: cluster

This is pRoloc version 1.12.4 
  Read '?pRoloc' and references therein for information
  about the package and how to get started.

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/pRoloc/plot2D.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plot2D
> ### Title: Plot organelle assignment data and results.
> ### Aliases: plot2D plot2Dmethods
> 
> ### ** Examples
> 
> library("pRolocdata")

This is pRolocdata version 1.10.0.
Use 'pRolocdata()' to list available data sets.
> data(dunkley2006)
> plot2D(dunkley2006, fcol = NULL)
> ## available methods
> plot2Dmethods
[1] "PCA"   "MDS"   "kpca"  "t-SNE" "none"  "scree"
> plot2D(dunkley2006, fcol = NULL, method = "kpca")
> plot2D(dunkley2006, fcol = NULL, method = "kpca",
+        methargs = list(kpar = list(sigma = 1)))
> plot2D(dunkley2006, fcol = "markers")
> addLegend(dunkley2006,
+           fcol = "markers",
+           where = "topright",
+           cex = 0.5, bty = "n", ncol = 3)
> title(main = "plot2D example")
> ## Using transparent colours
> setStockcol(paste0(getStockcol(), "80"))
> plot2D(dunkley2006, fcol = "markers")
> ## New behavious in 1.3.6 when not enough colours
> setStockcol(c("blue", "red", "green"))
> getStockcol() ## only 3 colours to be recycled
[1] "blue"  "red"   "green"
> getMarkers(dunkley2006)
organelleMarkers
     ER lumen   ER membrane         Golgi Mitochondrion            PM 
           14            45            28            55            46 
      Plastid      Ribosome           TGN       unknown       vacuole 
           20            19            13           428            21 
> plot2D(dunkley2006)
Not enough colours: using colours and pch.
> ## reset colours
> setStockcol(NULL)
> plot2D(dunkley2006, method = "none") ## plotting along 2 first fractions
> plot2D(dunkley2006, dims = c(3, 5), method = "none") ## plotting along fractions 3 and 5
> ## pre-calculate PC1 and PC2 coordinates
> pca <- plot2D(dunkley2006, plot=FALSE)
> head(pca)
          PC1 (64.36%) PC2 (22.34%)
AT1G09210    -4.734261   -0.8204175
AT1G21750    -4.615276   -1.1891468
AT1G51760    -4.770573   -1.6292717
AT1G56340    -5.318056   -0.9972462
AT2G32920    -5.135122   -1.5283630
AT2G47470    -4.899410   -0.8145343
> plot2D(pca, method = "none", methargs  = list(dunkley2006))
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>