The *R for Mass Spectrometry* project and meta-package
Laurent Gatto
de Duve Institute, UCLouvain, BelgiumSebastian Gibb
University Medicine Greifswald, GermanyJohannes Rainer
Eurac Research, Bolzano, ItalySource:
vignettes/RforMassSpectrometry.Rmd
RforMassSpectrometry.RmdIntroduction
RforMassSpectrometry is a meta-package, to manage and
document the R for Mass Spectrometry (https://www.rformassspectrometry.org/) project. The goal
of the project to provide efficient, thoroughly documented, tested and
flexible R software for the analysis and interpretation of high
throughput mass spectrometry assays, including proteomics and
metabolomics experiments. The project formalises the longtime
collaborative development efforts of its members under the R for
Mass Spectrometry organisation to facilitate dissemination and
accessibility of their work.
Installation
To install the core R for Mass Spectrometry packages, you will need
the BiocManager package, available on CRAN. If not already
available, install it with
if (!require("BiocManager"))
install.package("BiocManager")To proceed with the installation, run
BiocManager::install("RforMassSpectrometry/RforMassSpectrometry")Note that some very recent Bioconductor will be needed to install and run the suite of R for Mass Spectrometry packages, and will require a recent version of R and possibly even installing the Bioconductor development version.
Loading the RforMassSpectrometry package with
## Warning: replacing previous import 'MsCoreUtils::entropy' by 'Spectra::entropy'
## when loading 'RforMassSpectrometry'## Warning: replacing previous import 'MsCoreUtils::bin' by 'Spectra::bin' when
## loading 'RforMassSpectrometry'## Warning: replacing previous import 'MsCoreUtils::smooth' by 'Spectra::smooth'
## when loading 'RforMassSpectrometry'##
## Visit https://RforMassSpectrometry.org for detail about the project.will load the required core packages.
Code of Conduct
As contributors and maintainers of the R for Mass Spectrometry initiative, we pledge to respect all people who contribute through reporting issues, posting feature requests, updating documentation, submitting pull requests or patches, and other activities. We are committed to making participation in this project a harassment-free experience for everyone, regardless of level of experience, gender, gender identity and expression, sexual orientation, disability, personal appearance, body size, race, ethnicity, age, or religion. Examples of unacceptable behaviour by participants include the use of sexual language or imagery, derogatory comments or personal attacks, trolling, public or private harassment, insults, or other unprofessional conduct. Project maintainers have the right and responsibility to remove, edit, or reject comments, commits, code, wiki edits, issues, and other contributions that are not aligned to this Code of Conduct. Project maintainers who do not follow the Code of Conduct may be removed from the project team. Instances of abusive, harassing, or otherwise unacceptable behaviour may be reported by opening an issue or contacting one or more of the project maintainers.
This Code of Conduct is adapted from the Contributor Covenant, version 1.0.0, available from http://contributor-covenant.org/version/1/0/0/
As members of the Bioconductor community, we also abide by the Bioconductor code of conduct.
Contributions
The R for Mass Spectrometry project welcomes contributions in the form of ideas, documentation, code, packages, fixes (bugs and typos), … as pull requests (PR). We invite you to discuss any of these opening a GitHub issue in the relevant package github repository.
If you have any direct contributions to an existing package, we suggest to first discuss these in a dedicted issue if it implies any substantial changes (no need for an issue if its a simple typo, and we really appreciate those). If a non-trivial portion of your contribution is copied from somewhere else (such as AI-generated or copied from another software project) you are required to discuss it in the issue and disclose it in the PR description and provide details about the provenance (for example, ‘Assisted-by: Name of AI’ or ‘Code copied from: source’). Make sure to cite the provenance in the new code and that the newly contributed code can be redistributed under the software/packages licensing terms.
Contributions, even those from core members, are always expected to
come in the form of a PR that then undergoes a formal review. To do
this, start by forking the package you want to contribute. It is also
advised to work in, and make the PR, from a non-master branch. Good
branch names include issueX when it relates to a specific
issue, feat-X, bug-Y, docs-Z for
new features, bug fixes and documentation updates respectively. The
reviewers might ask for additional clarifications and/or changes prior
to merging the PR. When contemplating contributing code, please follow
the style guide below.
In particular, when several developers collaborate on a feature, an
admin should create a dedicated branch
RforMassSpectrometry/Package:branch. Developers should then
fetch that branch in their local copy of the Package
repository and send PRs to that branch too, where it will be reviewed,
and eventually merged into
RforMassSpectrometry/Package:master.
We also anticipate to open up some specific requests for contributions and invite specific members of the community, if we identify a specific need and/or a specific developer to address that need.
All R for Mass Spectrometry packages are released under open licences. Any contributions will have to adhere to these. If you cannot guarantee the provenance and legality of your contribution, please do not submit it as we won’t be able to accept it.
Reviewers will do their best to help you to get the PR merged1. See also the tidyverse contribution guide for additional resources and instructions.
Commit messages
Commit messages should follow the Conventional Commits guidelines. In particular, the following types are recommended (based on angulars types):
-
build:Changes that affect the build system or external dependencies (example scopes: depends, suggests, imports, …). -
ci:Changes to the continous integration (CI) configuration files and scripts (example: Travis configuration file). -
docs:Documentation only changes, including manual pages and vignettes. -
feat:A new feature. -
fix:A bug fix. -
perf:A code change that improves performance. -
refactor:A code change that neither fixes a bug nor adds a feature. -
style:Changes that do not affect the meaning of the code (white-space, formatting, …). -
test:Adding missing tests or correcting existing tests. -
other:Anything that doesn’t fit in the above. Consider opening an issue suggestion a new type.
Credit where credit is due
We also want to offer proper credit to those that provide substantial contributions. Substantial contributions include, for example
- new functionality that goes beyond e.g. a simple plot function
- bug fixes combined with related unit tests
- extended documentation, examples or vignettes describing a complete (potentially alternative) analysis workflow or use-case
Fixing typo(s) isn’t considered a substantial contribution per-se, even though they are highly appreciated.
Once a substantial contribution passes review and is merged, we will
add the contributor in the package’s author list as an official
contributor (ctb role) or even author (aut
role) for more substantial contributions. The contributors name will
also be added to the R for Mass Spectrometry web page and to
any relevant publications that directly stem from their work.
Coding style
The R for Mass Spectrometry packages follows the Bioconductor style guide. In particular
- Do not use
.when naming symbols. - A leading
.can be used for hidden/local functions or variables. - Snake case should be restricted to internal functions. For consistency, we favour camel case for public functions.
- Class names should start with a capital and each class should posses a constructor with identical name. Running the constructor without any input should produce a valid empty object.
- Use
##to start full-line comments. - For roxygen headers
#'is preferred, although##'is tolerated. - Use spaces between
=in function arguments or class definition:f(a = 1, b = 2). - Always use a space after a comma:
a, b, c. - Always use spaces around binary operators:
a + b. - Lines should be kept shorter than 80 characters. For example the following code isn’t accepted
# no wrap at 80
someVeryLongVariableName <- someVeryLongFunctionName(withSomeEvenLongerFunctionArgumentA = 1, withSomeEvenLongerFunctionArgumentB = 2)and should be wrapped as shown below:
# alternative 1
someVeryLongVariableName <-
someVeryLongFunctionName(withSomeEvenLongerFunctionArgumentA = 1,
withSomeEvenLongerFunctionArgumentB = 2)
# alternative 2
someVeryLongVariableName <- someVeryLongFunctionName(
withSomeEvenLongerFunctionArgumentA = 1,
withSomeEvenLongerFunctionArgumentB = 2)Contact
Please see the contact page for instructions on how to get in touch.
Session info
## R version 4.5.2 (2025-10-31)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 24.04.3 LTS
##
## Matrix products: default
## BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
## LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.26.so; LAPACK version 3.12.0
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
## [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
## [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
##
## time zone: UTC
## tzcode source: system (glibc)
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] RforMassSpectrometry_0.2.2 BiocStyle_2.38.0
##
## loaded via a namespace (and not attached):
## [1] SummarizedExperiment_1.40.0 MsExperiment_1.12.0
## [3] xfun_0.57 bslib_0.10.0
## [5] htmlwidgets_1.6.4 QFeatures_1.20.0
## [7] PSMatch_1.14.0 Biobase_2.70.0
## [9] lattice_0.22-9 PTMods_0.99.6
## [11] vctrs_0.7.3 tools_4.5.2
## [13] generics_0.1.4 stats4_4.5.2
## [15] parallel_4.5.2 tibble_3.3.1
## [17] cluster_2.1.8.2 pkgconfig_2.0.3
## [19] BiocBaseUtils_1.12.0 Matrix_1.7-5
## [21] desc_1.4.3 S4Vectors_0.48.1
## [23] lifecycle_1.0.5 compiler_4.5.2
## [25] stringr_1.6.0 textshaping_1.0.5
## [27] Seqinfo_1.0.0 codetools_0.2-20
## [29] clue_0.3-68 htmltools_0.5.9
## [31] sass_0.4.10 yaml_2.3.12
## [33] lazyeval_0.2.3 pillar_1.11.1
## [35] tidyr_1.3.2 pkgdown_2.2.0.9000
## [37] jquerylib_0.1.4 MASS_7.3-65
## [39] BiocParallel_1.44.0 cachem_1.1.0
## [41] DelayedArray_0.36.1 MetaboCoreUtils_1.18.1
## [43] abind_1.4-8 tidyselect_1.2.1
## [45] digest_0.6.39 stringi_1.8.7
## [47] purrr_1.2.2 dplyr_1.2.1
## [49] reshape2_1.4.5 bookdown_0.46
## [51] fastmap_1.2.0 grid_4.5.2
## [53] cli_3.6.6 SparseArray_1.10.10
## [55] magrittr_2.0.5 S4Arrays_1.10.1
## [57] rmarkdown_2.31 XVector_0.50.0
## [59] matrixStats_1.5.0 igraph_2.3.1
## [61] otel_0.2.0 ragg_1.5.2
## [63] evaluate_1.0.5 knitr_1.51
## [65] GenomicRanges_1.62.1 IRanges_2.44.0
## [67] MultiAssayExperiment_1.36.2 rlang_1.2.0
## [69] Rcpp_1.1.1-1.1 glue_1.8.1
## [71] DBI_1.3.0 BiocManager_1.30.27
## [73] BiocGenerics_0.56.0 Spectra_1.20.1
## [75] jsonlite_2.0.0 plyr_1.8.9
## [77] AnnotationFilter_1.34.0 R6_2.6.1
## [79] MatrixGenerics_1.22.0 systemfonts_1.3.2
## [81] fs_2.1.0 ProtGenerics_1.42.0
## [83] MsCoreUtils_1.25.4