Package 'RforProteomics' reference manual

Title:	Companion package to the 'Using R and Bioconductor for proteomics data analysis' publication
Description:	This package contains code to illustrate the 'Using R and Bioconductor for proteomics data analysis' and 'Visualisation of proteomics data using R and Bioconductor' manuscripts. The vignettes describe the code and data needed to reproduce the examples and figures described in the paper and functionality for proteomics visualisation. It also contain various function to discover R software for mass spectrometry and proteomics.
Authors:	Laurent Gatto [aut, cre], Sebastian Gibb [ctb], Vlad Petyuk [ctb], Thomas Pedersen Lin [ctb]
Maintainer:	Laurent Gatto <[email protected]>
License:	Artistic-2.0
Version:	1.50.0
Built:	2026-10-10 11:07:20 UTC
Source:	https://github.com/bioc/RforProteomics

Download a file

Description

Unless already present, downloads src in the destdir directory.

Usage

downloadData(src, destdir = ".", unpack = TRUE, ...)
downloadData(src, destdir = ".", unpack = TRUE, ...)

Arguments

src

The url of the file to download.

destdir

The destination directory. Default is ".".

unpack

Should src be uncompressed? Default is TRUE.

...

Additional paramters passed to download.file.

Value

Invisible returns the full path of the downloaded file.

Author(s)

Laurent Gatto

Packages in a biocView

Description

Finds the package names that have a specific biocView.

Usage

getPackagesInBiocView(
  view,
  rep = c("BioCsoft", "BioCann", "BioCexp", "BioCextra"),
  biocVersion
)
getPackagesInBiocView(
  view,
  rep = c("BioCsoft", "BioCann", "BioCexp", "BioCextra"),
  biocVersion
)

Arguments

view

The biocView of interest. For example "Proteomics".

rep

Repository of interest. One of "BioCsoft", "BioCann", "BioCexp" or '"BioCextra"1.

biocVersion

A character with the Bioconductor version of interest. For example "2.14".

Value

An instance of class BiocView. NULL if the the biocView was not found.

Author(s)

Laurent Gatto

Download the PXD000001 mzTab file

Description

Unless already present, downloads the PXD000001 mzData file in the destdir directory. The resulting file is named PRIDE_Exp_Complete_Ac_22134.xml

Usage

getPXD000001mzData(destdir = ".")
getPXD000001mzData(destdir = ".")

Arguments

destdir

A character with the destination folder.

Value

Invisibly returns the name of the downloaded file.

Author(s)

Laurent Gatto

Download the PXD000001 mzTab file

Description

Unless already present, downloads the PXD000001 mzTab file in the destdir directory. The resulting file is named F063721.dat-mztab.txt.

Usage

getPXD000001mzTab(destdir = ".")
getPXD000001mzTab(destdir = ".")

Arguments

destdir

A character with the destination folder.

Value

Invisibly returns the name of the downloaded file.

Author(s)

Laurent Gatto

Download the PXD000001 mzXML file

Description

Unless already present, downloads the PXD000001 mzXML file in the destdir directory. The resulting file is named TMT_Erwinia_1uLSike_Top10HCD_isol2_45stepped_60min_01.mzXML.

Usage

getPXD000001mzXML(destdir = ".")
getPXD000001mzXML(destdir = ".")

Arguments

destdir

A character with the destination folder.

Value

Invisibly returns the name of the downloaded file.

Author(s)

Laurent Gatto

The name of the file to be downloaded. If missing, a vector of possible filenames is returned. If "all", all files are downloaded. Alternatively, a pattern can be used to grep the files from the output getThermoHelaPRTC() the files to be downloaded.

destdir

Destination directory. Default is ".".

Value

Invisibly return the path of the downloaded files.

Author(s)

Laurent Gatto

Examples

## Not run: 
getThermoHelaPRTC()
getThermoHelaPRTC("design")
getThermoHelaPRTC("all")

## End(Not run)
## Not run: 
getThermoHelaPRTC()
getThermoHelaPRTC("design")
getThermoHelaPRTC("all")

## End(Not run)

An `mzIdentML` file

Description

This file has been generated by searching the raw mzXML file of the ProteomeXchange PXD000001 data set against the erwinia_carotovora.fasta using the MSGF+ search engine: java -jar ~/bin/MSGFPlus.20140630/MSGFPlus.jar -s TMT_Erwinia_1uLSike_Top10HCD_isol2_45stepped_60min_01.mzXML -d erwinia_carotovora.fasta -inst 1 -protocol 2

Examples

## source files to repeat the search
library("rpx")
px <- PXDataset("PXD000001")
pxfiles(px)

f <- dir(system.file("extdata", package = "RforProteomics"),
         pattern = "mzid", full.names=TRUE)
library("mzID")
id <- mzID(f)
id
## source files to repeat the search
library("rpx")
px <- PXDataset("PXD000001")
pxfiles(px)

f <- dir(system.file("extdata", package = "RforProteomics"),
         pattern = "mzid", full.names=TRUE)
library("mzID")
id <- mzID(f)
id

Create, analyse and detect ions

Description

This is the constructor function to generate a set of ions that can later be analysed with 'analyse()' and detected with 'detect()'.

Usage

new_ions(npeaks = 10, mzrange = c(100, 1000), nimg = 100)

analyse(x, sleep = 0.1)

analyze(x, sleep = 0.1)

detect(x, new = FALSE)

spectrum(x, ...)
new_ions(npeaks = 10, mzrange = c(100, 1000), nimg = 100)

analyse(x, sleep = 0.1)

analyze(x, sleep = 0.1)

detect(x, new = FALSE)

spectrum(x, ...)

Arguments

npeaks

A 'numeric' scalar defining the number of unique peaks (M/Z values). Default is 10.

mzrange

A 'numeric' of length 2 defining the range of possible M/Z values. Default is 'c(100, 1000)'.

nimg

A 'numeric' scalar. When analysing the ions, their separation along their M/Z values will be split along a sequence of length 'nimg'. Default is 100.

x

An object of class 'ions'.

sleep

How much time to wait before producing the next plot.

new

A 'logical' scalar, indicating if the separated ions (last frame of calling 'analyse) should be plotting, or whether the detection should be overlaid. Default is 'FALSE', to add the plot on top of the opened device.

...

Additional arguments passed to [graphics::plot()].

Value

An object of class 'ions'.

'analyse', 'detect' and 'spectrum' are used for their side effect or producing plots. They all invisibly return 'NULL'.

Author(s)

Laurent Gatto

Examples

set.seed(1L)
x <- new_ions(nimg = 5)
x
analyse(x)
detect(x)
spectrum(x)
set.seed(1L)
x <- new_ions(nimg = 5)
x
analyse(x)
detect(x)
spectrum(x)

Package descriptions

Description

Format a BiocView as a data.frame.

Usage

packageDF(x, nsub = TRUE, version = TRUE)
packageDF(x, nsub = TRUE, version = TRUE)

Arguments

x

An instance of class BiocView, as produced by getPackagesInBiocView.

nsub

A logical indicating "\n" are to be replaced by a space.

version

A logical specifying if the package version should be added.

Value

A data.frame with package information.

Author(s)

Laurent Gatto

Proteomics and MS biocView packages

Description

Searches for all the packages with the "Proteomics" (software), "MassSpectrometry" (software) and "MassSepctrometryData" (data) packages and return their names, titles and versions as a data.frame. The (unexported but documented) underlying functions are RforProteomics:::getPackagesInBiocView (to find relevant package) and RforProteomics:::packageDF (data.frame formatting).

Usage

proteomicsPackages(biocv, cache = FALSE)

massSpectrometryPackages(biocv, cache = FALSE)

massSpectrometryDataPackages(biocv, cache = FALSE)
proteomicsPackages(biocv, cache = FALSE)

massSpectrometryPackages(biocv, cache = FALSE)

massSpectrometryDataPackages(biocv, cache = FALSE)

Arguments

biocv

A character with the Bioconductor version to search for relevant packages. If missing, the running version is used.

cache

A logical indicating whether cached package information should be used. Default is FALSE. All except development versions are up-to-date.

Value

A data.frame with the respective package names, titles and versions.

Author(s)

Laurent Gatto

Examples

head(pp <- proteomicsPackages("3.0"))
ppc <- proteomicsPackages("3.0", cache = TRUE)
all.equal(pp, ppc)
head(pp <- proteomicsPackages("3.0"))
ppc <- proteomicsPackages("3.0", cache = TRUE)
all.equal(pp, ppc)

PXD000001 example MSnSet

Description

In this TMT 6-plex experiment, four exogenous proteins were spiked into an equimolar Erwinia carotovora lysate with varying proportions in each channel of quantitation; yeast enolase (ENO) at 10:5:2.5:1:2.5:10, bovine serum albumin (BSA) at 1:2.5:5:10:5:1, rabbit glycogen phosphorylase (PHO) at 2:2:2:2:1:1 and bovin cytochrome C (CYT) at 1:1:1:1:1:2. Proteins were then digested, differentially labelled with TMT reagents, fractionated by reverse phase nanoflow UPLC (nanoACQUITY, Waters), and analysed on an LTQ Orbitrap Velos mass spectrometer (Thermo Scientific). Files in multiple format will be used to illustrate the input/output capabilities that are available to the proteomics audience. The companion package provides dedicated functions to directly download the data.

The data has been downloaded from the ProteomeXchange repository and imported into R as illustrated in the example. It is of class MSnSet. See also the MSnbase-demo vignette for more details.

Usage

data("qnt")data("qnt")

Format

An instance of class MSnSet

References

Laurent Gatto (2014). RforProteomcs: Companion package to the 'Using R and Bioconductor for proteomics data analysis' publicationR package version 1.3.1.

Gatto L, Christoforou A. Using R and Bioconductor for proteomics data analysis. Biochim Biophys Acta. 2013 May 18. doi:pii: S1570-9639(13)00186-6. 10.1016/j.bbapap.2013.04.032. [Epub ahead of print] PubMed PMID: 23692960.

Examples


## Not run: 
    library("rpx")
    px1 <- PXDataset("PXD000001")
    mztab <- pxget(px1, "PXD000001_mztab.txt")
    library("MSnbase")
    qnt <- readMzTabData(mztab, what = "PEP")
    sampleNames(qnt) <- reporterNames(TMT6)
    qnt$conditions <- factor(c("A", "A", "B", "B", "B", "A"))
    qnt <- filterNA(qnt)

    selA <- qnt$conditions == "A"

    fData(qnt)$log2FC <-
        log(rowMeans(exprs(qnt)[, selA]), 2) -
            log(rowMeans(exprs(qnt)[, !selA]), 2)
    fData(qnt)$baseMean <- log(rowMeans(exprs(qnt)), 10)

## End(Not run)

library("RforProteomics")
library("MSnbase")
data(qnt)
class(qnt)
head(exprs(qnt))
head(fData(qnt))
## Not run: 
    library("rpx")
    px1 <- PXDataset("PXD000001")
    mztab <- pxget(px1, "PXD000001_mztab.txt")
    library("MSnbase")
    qnt <- readMzTabData(mztab, what = "PEP")
    sampleNames(qnt) <- reporterNames(TMT6)
    qnt$conditions <- factor(c("A", "A", "B", "B", "B", "A"))
    qnt <- filterNA(qnt)

    selA <- qnt$conditions == "A"

    fData(qnt)$log2FC <-
        log(rowMeans(exprs(qnt)[, selA]), 2) -
            log(rowMeans(exprs(qnt)[, !selA]), 2)
    fData(qnt)$baseMean <- log(rowMeans(exprs(qnt)), 10)

## End(Not run)

library("RforProteomics")
library("MSnbase")
data(qnt)
class(qnt)
head(exprs(qnt))
head(fData(qnt))

Opens the package vignettes

Description

Opens the package and visualisation vignettes.

Usage

RforProteomics()

RProtVis()

RProtViz()
RforProteomics()

RProtVis()

RProtViz()

Value

An instance of class vignette. Used for its side effect, opening a vignette.

Author(s)

Laurent Gatto

Package 'RforProteomics'

Help Index

Download a file

Description

Usage

Arguments

Value

Author(s)

Packages in a biocView

Description

Usage

Arguments

Value

Author(s)

Download the PXD000001 mzTab file

Description

Usage

Arguments

Value

Author(s)

Download the PXD000001 mzTab file

Description

Usage

Arguments

Value

Author(s)

Download the PXD000001 mzXML file

Description

Usage

Arguments

Value

Author(s)

Dowload Thermo Hela PRTC data

Description

Usage

Arguments

Value

Author(s)

See Also

Examples

An mzIdentML file

Description

Examples

Create, analyse and detect ions

Description

Usage

Arguments

Value

Author(s)

Examples

Package descriptions

Description

Usage

Arguments

Value

Author(s)

Proteomics and MS biocView packages

Description

Usage

Arguments

Value

Author(s)

Examples

PXD000001 example MSnSet

Description

Usage

Format

References

Examples

Opens the package vignettes

Description

Usage

Value

Author(s)

An `mzIdentML` file