Data from Nikolovski et al. 2012

Description

This is the data used in Nikolovksi et al. (2012). See below for details and references.

Usage

data(nikolovski2012)
data(nikolovski2012imp)

Format

The data is an instance of class MSnSet from package MSnbase.

Details

These data are a concatenation of 4 LOPIT experiments. Experiments 1 and 2 are from Dunkley et al. 2006 (see also dunkley2006). Exepriments 3 and 4 are new.

In the LOPIT experiments by Dunkley et al. (2006), peripheral membrane proteins were removed by carbonate washing of the isolated membranes, while for experiments 3 and 4, no carbonate wash was performed and are, as such, enriched in peripheral and luminal proteins. See figure 1 in Nikolovski 2012 for a description of the design.

In nikolovksi2012imp missing values have been imputed using partial least-squares regression.

The training set used for the Naive Bayesian classifier is available as the markers feature meta-data. Note that Nikolovksi included a group of markers labelled 'others', which has been retained in these data sets. The results produced in this work are available in the preds feature variable (note that some organelles are marked with a '*', which is undefined here).

Source

Supporting Information on http://www.plantphysiol.org/content/160/2/1037.long, also available in the package's extdata directory.

References

Nikolovski N, Rubtsov D, Segura MP, Miles GP, Stevens TJ, Dunkley TP, Munro S, Lilley KS, Dupree P. Putative glycosyltransferases and other plant Golgi apparatus proteins are revealed by LOPIT proteomics. Plant Physiol. 2012 Oct;160(2):1037-51. doi: 10.1104/pp.112.204263. Epub 2012 Aug 24. PMID: 22923678; PMCID: PMC3461528.

Dunkley TP, Hester S, Shadforth IP, Runions J, Weimar T, Hanton SL, Griffin JL, Bessant C, Brandizzi F, Hawes C, Watson RB, Dupree P, Lilley KS. Mapping the Arabidopsis organelle proteome. Proc Natl Acad Sci U S A. 2006 Apr 25;103(17):6518-23. Epub 2006 Apr 17. PubMed PMID: 16618929; PubMed Central PMCID: PMC1458916.

Examples

data(nikolovski2012)
data(nikolovski2012imp)
table(is.na(nikolovski2012))
table(is.na(nikolovski2012imp))
phenoData(nikolovski2012)
table(fData(nikolovski2012)$markers)
all.equal(sort(featureNames(nikolovski2012)),
          sort(featureNames(nikolovski2012imp)))
library("pRoloc")
plot2D(nikolovski2012imp)
addLegend(nikolovski2012imp, where = "topright", bty = "n", cex =.7)

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(pRolocdata)
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


This is pRolocdata version 1.10.0.
Use 'pRolocdata()' to list available data sets.
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/pRolocdata/nikolovski2012.Rd_%03d_medium.png", width=480, height=480)
> ### Name: nikolovski2012
> ### Title: Data from Nikolovski et al. 2012
> ### Aliases: nikolovski2012 nikolovski2012imp
> ### Keywords: datasets
> 
> ### ** Examples
> 
> data(nikolovski2012)
> data(nikolovski2012imp)
> table(is.na(nikolovski2012))

FALSE  TRUE 
31096 13224 
> table(is.na(nikolovski2012imp))

FALSE 
44320 
> phenoData(nikolovski2012)
An object of class 'AnnotatedDataFrame'
  rowNames: LOPIT1A_114 LOPIT1A_115 ... LOPIT4B_117 (32 total)
  varLabels: experiment replicate ... original (5 total)
  varMetadata: labelDescription
> table(fData(nikolovski2012)$markers)

           ER     Golgi/TGN Mitochondrion         Other            PM 
           53            41            92            72            39 
      Plastid       Vacuole       unknown 
           40            11          1037 
> all.equal(sort(featureNames(nikolovski2012)),
+           sort(featureNames(nikolovski2012imp)))
[1] TRUE
> library("pRoloc")
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.

> plot2D(nikolovski2012imp)
> addLegend(nikolovski2012imp, where = "topright", bty = "n", cex =.7)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>