Displays a spatial proteomics animation

Description

Given two MSnSet instances of one MSnSetList with at least two items, this function produces an animation that shows the transition from the first data to the second.

Usage

move2Ds(object, pcol, fcol = "markers", n = 25, hl)

Arguments

Value

Used for its side effect of producing a short animation.

Author(s)

Laurent Gatto

See Also

plot2Ds to a single figure with the two datasets.

Examples

library("pRolocdata")
data(dunkley2006)

## Create a relevant MSnSetList using the dunkley2006 data
xx <- split(dunkley2006, "replicate")
xx1 <- xx[[1]]
xx2 <- xx[[2]]
fData(xx1)$markers[374] <- "Golgi"
fData(xx2)$markers[412] <- "unknown"
xx@x[[1]] <- xx1
xx@x[[2]] <- xx2

## The features we want to track
foi <- FeaturesOfInterest(description = "test",
                          fnames = featureNames(xx[[1]])[c(374, 412)])

## (1) visualise each experiment separately
par(mfrow = c(2, 1))
plot2D(xx[[1]], main = "condition A")
highlightOnPlot(xx[[1]], foi)
plot2D(xx[[2]], mirrorY = TRUE, main = "condition B")
highlightOnPlot(xx[[2]], foi, args = list(mirrorY = TRUE))

## (2) plot both data on the same plot
par(mfrow = c(1, 1))
tmp <- plot2Ds(xx) 
highlightOnPlot(data1(tmp), foi, lwd = 2)
highlightOnPlot(data2(tmp), foi, pch = 5, lwd = 2)

## (3) create an animation
move2Ds(xx, pcol = "replicate")
move2Ds(xx, pcol = "replicate", hl = foi)

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(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/move2Ds.Rd_%03d_medium.png", width=480, height=480)
> ### Name: move2Ds
> ### Title: Displays a spatial proteomics animation
> ### Aliases: move2Ds
> 
> ### ** Examples
> 
> library("pRolocdata")

This is pRolocdata version 1.10.0.
Use 'pRolocdata()' to list available data sets.
> data(dunkley2006)
> 
> ## Create a relevant MSnSetList using the dunkley2006 data
> xx <- split(dunkley2006, "replicate")
> xx1 <- xx[[1]]
> xx2 <- xx[[2]]
> fData(xx1)$markers[374] <- "Golgi"
> fData(xx2)$markers[412] <- "unknown"
> xx@x[[1]] <- xx1
> xx@x[[2]] <- xx2
> 
> ## The features we want to track
> foi <- FeaturesOfInterest(description = "test",
+                           fnames = featureNames(xx[[1]])[c(374, 412)])
> 
> ## (1) visualise each experiment separately
> par(mfrow = c(2, 1))
> plot2D(xx[[1]], main = "condition A")
> highlightOnPlot(xx[[1]], foi)
> plot2D(xx[[2]], mirrorY = TRUE, main = "condition B")
> highlightOnPlot(xx[[2]], foi, args = list(mirrorY = TRUE))
> 
> ## (2) plot both data on the same plot
> par(mfrow = c(1, 1))
> tmp <- plot2Ds(xx) 
> highlightOnPlot(data1(tmp), foi, lwd = 2)
> highlightOnPlot(data2(tmp), foi, pch = 5, lwd = 2)
> 
> ## (3) create an animation
> move2Ds(xx, pcol = "replicate")
> move2Ds(xx, pcol = "replicate", hl = foi)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>