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rforproteomics's Introduction

Introduction

The RforProteomics package distributes and extends the use-cases described in the Using R and Bioconductor for proteomics data analysis manuscript (pubmed and pre-print). The package illustrates how R and a selection of dedicated packages that can be used to access mass-spectrometry proteomics data, manipulate and visualise it, how to process label-free and labelled quantitative data and how to analyse the quantitation data.

The package will be updated beyond the content of the manuscript to keep up-to-date with progress in the area. The github page can be used to edit the wiki and file new issues related to the package itself of general needed for proteomics that should be addressed in R.

NB: I you are interested in R packages for mass spectrometry-based proteomics and metabolomics, see also the R for Mass Spectrometry initiative packages and the tutorial book

It would be great if this work could stimulate a wider participation to use R and develop R packages for proteomics and promote interaction between computational biologists working in the field of proteomics, in particular by facilitating interoperability between their software. The official Bioconductor support site is the channel of choice to ask questions about specific Bioconductor packages.

Data and vignette

The package uses the dataset PXD000001 from the ProteomeXchange repository in several examples. The data can be queried and downloaded from R with the rpx package. The RforProteomics vignette is a detailed document containing the exact code to reproduce all the analyses presented in the manuscript as well as other application examples. It can be accessed once the package is installed (see below) with the RforProteomics() function. Alternatively, the vignettes can be read online here and here.

A second vignette, RProtVis focuses on the visualisation of mass spectrometry and proteomics data with R and Bioconductor. From R, it is currently only available with Bioconductor >= 3.0 using the RProtViz() function. It can also be consulted on-line on the 'RforProteomics' development version page.

Installation

The package is available on Bioconductor (version >= 2.13). To install the package and its documentation, start R (>= 3.0.0 required) and type:

if (!requireNamespace("BiocManager", quietly=TRUE))
    install.packages("BiocManager")
BiocManager::install("RforProteomics")

To install all dependencies (75+ packages, including RforProteomics) and fully reproduce the code in the vignettes, replace the last line in the code chunk above with:

BiocManager::install("RforProteomics", dependencies = TRUE)

Collaborative editing

The community and package authors are invited to contribute to the package. If you have or know of a package of interest, please fork the repository, add a new section to the vignette and send a pull request. If you update the vignette, please also add yourself as a contributor to the package.

Help

To obtain help or additional information about the RforProteomics package and about the packages presented in the vignette or manuscript, please use the Bioconductor support site.

For general resources about R, see the corresponding section in the vignettes and the TeachingMaterial repository.

rforproteomics's People

Contributors

dtenenba avatar hpages avatar jwokaty avatar laurentgatto avatar lgatto avatar link-ny avatar lshep avatar nturaga avatar sgibb avatar sonali-bioc avatar svalvaro avatar thomasp85 avatar vladpetyuk avatar

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rforproteomics's Issues

msDataTab

The MS data table currently looks like this.

Data type File format Data structure Package
Raw mzXML or mzML mzRpwiz or mzRramp mzR
Raw mzXML or mzML List of MassSpectrum objects MALDIquantForeign
Identification mzIdentML mzRident mzR
Identification mzIdentML mzID mzID
Quantitative mzTab MSnSet MSnbase
Raw mzXML or mzML MSnExp MSnbase
Peak lists mgf MSnExp MSnbase
Imaging imzML or Analyze 7.5 MSImageSet or list of MassSpectrum objects Cardinal or MALDIquantForeign

@sgibb could you split Cardinal and MALDIquantForeign on two different lines, as I have done for raw data, as the table becomes unnecessary wide like it is now (see the chapter for example).

Loading .txt file in RforProteomics

Sir,
I was trying to load the attached Mass spectrometry output file in Rforproteomics using openMSfile but getting this:

> ms1=openMSfile('proteinGroups_166_Bioinf.txt')
Error in .mzRBackendFromContent(x) : 
  Could not determine file type for proteinGroups_166_Bioinf.txt

Any help? I am new in this topic.
Best Regards
Zillur
proteinGroups_166_Bioinf.txt

> sessionInfo()
R version 4.0.2 (2020-06-22)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19041)

Matrix products: default

locale:
[1] LC_COLLATE=English_United States.1252 
[2] LC_CTYPE=English_United States.1252   
[3] LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C                          
[5] LC_TIME=English_United States.1252    

attached base packages:
[1] stats4    parallel  stats     graphics  grDevices utils     datasets 
[8] methods   base     

other attached packages:
 [1] RforProteomics_1.26.0 MSnbase_2.14.2        ProtGenerics_1.20.0  
 [4] S4Vectors_0.26.1      mzR_2.22.0            Rcpp_1.0.5           
 [7] Biobase_2.48.0        BiocGenerics_0.34.0   edgeR_3.30.3         
[10] limma_3.44.3          XML_3.99-0.5         

loaded via a namespace (and not attached):
 [1] locfit_1.5-9.4        lattice_0.20-41       digest_0.6.25        
 [4] foreach_1.5.0         mime_0.9              R6_2.4.1             
 [7] plyr_1.8.6            mzID_1.26.0           ggplot2_3.3.2        
[10] pillar_1.4.6          biocViews_1.56.2      zlibbioc_1.34.0      
[13] rlang_0.4.7           rstudioapi_0.11       R.utils_2.10.1       
[16] R.oo_1.24.0           RUnit_0.4.32          preprocessCore_1.50.0
[19] BiocParallel_1.22.0   RCurl_1.98-1.2        munsell_0.5.0        
[22] shiny_1.5.0           compiler_4.0.2        httpuv_1.5.4         
[25] pkgconfig_2.0.3       pcaMethods_1.80.0     htmltools_0.5.0      
[28] tidyselect_1.1.0      tibble_3.0.3          IRanges_2.22.2       
[31] codetools_0.2-16      crayon_1.3.4          dplyr_1.0.2          
[34] later_1.1.0.1         bitops_1.0-6          MASS_7.3-51.6        
[37] R.methodsS3_1.8.1     grid_4.0.2            RBGL_1.64.0          
[40] xtable_1.8-4          gtable_0.3.0          lifecycle_0.2.0      
[43] affy_1.66.0           magrittr_1.5          scales_1.1.1         
[46] ncdf4_1.17            graph_1.66.0          impute_1.62.0        
[49] promises_1.1.1        affyio_1.58.0         doParallel_1.0.15    
[52] ellipsis_0.3.1        generics_0.0.2        vctrs_0.3.4          
[55] iterators_1.0.12      tools_4.0.2           glue_1.4.2           
[58] purrr_0.3.4           fastmap_1.0.1         colorspace_1.4-1     
[61] BiocManager_1.30.10   vsn_3.56.0            MALDIquant_1.19.3   

Adding packages and examples

Packages to add to the RforProteomics vignette:

From Bioc:

  • msmsEDA and msmsTests
  • MSstats

From CRAN:

  • isopat: Calculation of isotopic pattern for a given molecular formula
  • protiq: Protein (identification and) quantification based on peptide evidence - also contains SCAMPI
  • aLFQ An R-package for estimating absolute protein quantities from label-free LC-MS/MS proteomics data - ref
  • protViz: Visualizing and Analyzing Mass Spectrometry Related Data in Proteomics

Other:

  • EBprot Bayesian Analysis of labeling-based Quantitative Proteomics Data - ref

Possibly get in touch with authors, and ask them to contribute a short section to the vignette?

plotOutput is called with deprecated clickId parameter

When running a reverse dependency check on the development version of Shiny, which we are about to release, we see:

✖ RforProteomics 1.26.0                  ── E: 0     | W: 1     | N: 2  +1                                                                                                     
  * checking R code for possible problems ... NOTE
    
    shinyMA: possible error in plotOutput("plotma", clickId =
      "plotma_click", width = 400, height = 400): unused argument (clickId
      = "plotma_click")

The clickId parameter was deprecated 5 years ago, and we recently removed it.
rstudio/shiny#2834

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