pRoloc (version 1.12.4)

plot2D: 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.

Value

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

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.

See Also

addLegend to add a legend to plot2D figures and plotDist for alternative graphical representation of quantitative organelle proteomics data. plot2Ds to overlay 2 data sets on the same PCA plot.

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))