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diagFDR: Assessing False Discovery Rate Claims in Proteomics

Provides scope, calibration and stability diagnostics to assess false discovery rate (FDR) claims in peptide and protein identification workflows based on target-decoy competition and related confidence measures. Includes the recomputed decoy ratio of the reported list, accepted decoy counts and local decoy support, threshold elasticity, posterior error probability (PEP) concordance with the decoys, equal-chance checks and p-value calibration, with an HTML report. If you used this package in your research, please cite the associated preprint <doi:10.64898/2026.04.16.718468>. Detailed examples of using this package can also be found on the GitHub repository (<https://github.com/Jacky11/diagFDR>).

Version: 0.1.2
Depends: R (≥ 4.2.0)
Imports: dplyr, tibble, ggplot2, purrr, rlang, readr, xml2, cp4p, tidyr, scales, data.table
Suggests: arrow, knitr, officer, rvg, testthat (≥ 3.0.0), withr, rmarkdown, jsonlite
Published: 2026-10-19
DOI: 10.32614/CRAN.package.diagFDR
Author: Quentin Giai Gianetto [aut, cre]
Maintainer: Quentin Giai Gianetto <quentin.giaigianetto at pasteur.fr>
License: GPL-3
URL: https://www.biorxiv.org/content/10.64898/2026.04.16.718468
NeedsCompilation: no
Materials: NEWS
CRAN checks: diagFDR results

Documentation:

Reference manual: diagFDR.html , diagFDR.pdf
Vignettes: diagFDR: DIA-NN diagnostics from report.parquet (source, R code)
diagFDR: MaxQuant diagnostics from msms.txt (source, R code)
diagFDR: mokapot diagnostics (competed winners) (source, R code)
diagFDR: generic PSM diagnostics from mzIdentML (.mzid) (source, R code)
diagFDR: generic elution groups diagnostics from Spectronaut (tsv report) (source, R code)

Downloads:

Package source: diagFDR_0.1.2.tar.gz
Windows binaries: r-devel: diagFDR_0.1.2.zip, r-release: diagFDR_0.1.2.zip, r-oldrel: diagFDR_0.1.2.zip
macOS binaries: r-release (arm64): diagFDR_0.1.2.tgz, r-oldrel (arm64): diagFDR_0.1.2.tgz, r-release (x86_64): diagFDR_0.1.2.tgz, r-oldrel (x86_64): diagFDR_0.1.2.tgz
Old sources: diagFDR archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=diagFDR to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.