Dataset - Proteomics Data to accompany "Assessing Degenerate Peptide Resolution Methods using a Ground Truth Dataset"

download Download
Integrative Omics
Microbiome Science

This data package contains processed LC-MS proteomics results and analysis scripts associated with the paper "Assessment of Protein Inference Methods for Metaproteomics". In this study, we designed an artificial microbial community to create a simulated metaproteomic dataset which intentionally includes degenerate peptides to enable evaluation of different protein inference methods. This data product includes peptide identifications and confidence scores from our primary and secondary benchmarking datasets, as well as the code used for analysis.

Contents (1.22GB)

Data

  • 4998_Benchmarking_Dataset_I

    • FASTAs: 11 FASTA files digested in silico to create the reference library.
    • e_data_4998.csv: Peptide expression data by sample.
    • e_meta_4998.csv: Peptide metadata, including protein mappings.
    • f_data_4998.csv: Experiment metadata, including sample groupings.
    • scores_4998.csv: Peptide identification confidence scores from the search tool, MS-GF+.
    • msnid_4998.RDS:  Peptide identifications in MSnID format, saved as an R data object.
    • Benchmarking_Dataset_I.csv: Compiled labeled dataset. See README
    • README
  • 5765_Benchmarking_Dataset_II
    • (the same files as above, for the second dataset)

Code

  • peptide_analysis_with_figures_BJM_Aug2026.Rmd: Script used for analysis and figure generation.
  • R_session_info.txt: Environment information, including software package versions.
  • Rmarkdown_complete.Rdata: R environment containing all objects present after running the analysis script. Included to avoid rerunning code chunks that take several hours.

License

This data product is licensed under a Creative Commons Zero (“CC0”) Public Domain Dedication Waiver (https://creativecommons.org/publicdomain/zero/1.0/) in accordance with PNNL DataHub policy (https://data.pnnl.gov/policy).

 

Version History

01 September 2026: Updated language to reflect terms used in manuscript resubmission. Improved figure resolution and clarified axis labels etc. Added labeled data matrix and corresponding README.

02 November 2025: initial publication on PNNL DataHub

English