DBCLS BioHackathon 2026 report: Mass spectrometry data analysis workflow and visualization towards trans-omics research
Abstract
Public repositories for mass spectrometry (MS) data contain rapidly growing collections of proteomic, metaproteomic, and metabolomic data, but differences in analytical procedures, metadata, data formats, and visualization environments limit their reuse and integration. During BioHackathon 2026, we developed complementary components of an infrastructure for standardized reanalysis for proteomics and trans-omics applications. First, we redesigned the jPOST proteomics reanalysis workflow to improve scalability, reduce manual intervention, and facilitate consistent transfer of data and metadata among the repository, reanalysis system, and jPOSTdb. The workflow uses detailed Journal of Proteome Data and Methods (JPDM) metadata and integrates results from three search engines using UniScore. Second, we developed metaproteome visualizations that connect spectral evidence with metabolic pathways and microbial phyla, enabling functional comparison among samples and experimental groups. Third, we enhanced Mass++4, a cross-platform spectrum and chromatogram viewer, by improving its connectivity with public repositories and expanding functions relevant to the inspection of proteomic and metabolomic data. Finally, we investigated the interoperability of MB-POST with the MetabolomicsHub common data model and mzTab-M. This analysis identified requirements for controlled-vocabulary mapping, explicit representation of experimental factors and sample groups, and standardization of quantitative-result formats. Together, these developments connect raw-data preservation, standardized metadata, reproducible reanalysis, biological visualization, and cross-repository interoperability. Although further implementation and large-scale validation are required, they provide a practical foundation for integrating proteomic, metaproteomic, and metabolomic data in future trans-omics studies.
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BibTeX
@misc{goto2026dbcls,
title = {{DBCLS BioHackathon 2026 report: Mass spectrometry data analysis workflow and visualization towards trans-omics research}},
author = {Susumu Goto and Akiyasu C. Yoshizawa and Yuki Moriya and Kozo Nishida and Yushi Takahashi and Satoshi Tanaka and Shin Kawano},
howpublished = {BioHackrXiv},
year = {2026},
month = oct,
doi = {10.37044/osf.io/76thg_v1},
url = {https://osf.io/preprints/biohackrxiv/76thg_v1/},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - DBCLS BioHackathon 2026 report: Mass spectrometry data analysis workflow and visualization towards trans-omics research
AU - Susumu Goto
AU - Akiyasu C. Yoshizawa
AU - Yuki Moriya
AU - Kozo Nishida
AU - Yushi Takahashi
AU - Satoshi Tanaka
AU - Shin Kawano
PY - 2026
DA - 2026/10/21
PB - BioHackrXiv
DO - 10.37044/osf.io/76thg_v1
UR - https://osf.io/preprints/biohackrxiv/76thg_v1/
AB - Public repositories for mass spectrometry (MS) data contain rapidly growing collections of proteomic, metaproteomic, and metabolomic data, but differences in analytical procedures, metadata, data formats, and visualization environments limit their reuse and integration. During BioHackathon 2026, we developed complementary components of an infrastructure for standardized reanalysis for proteomics and trans-omics applications. First, we redesigned the jPOST proteomics reanalysis workflow to improve scalability, reduce manual intervention, and facilitate consistent transfer of data and metadata among the repository, reanalysis system, and jPOSTdb. The workflow uses detailed Journal of Proteome Data and Methods (JPDM) metadata and integrates results from three search engines using UniScore. Second, we developed metaproteome visualizations that connect spectral evidence with metabolic pathways and microbial phyla, enabling functional comparison among samples and experimental groups. Third, we enhanced Mass++4, a cross-platform spectrum and chromatogram viewer, by improving its connectivity with public repositories and expanding functions relevant to the inspection of proteomic and metabolomic data. Finally, we investigated the interoperability of MB-POST with the MetabolomicsHub common data model and mzTab-M. This analysis identified requirements for controlled-vocabulary mapping, explicit representation of experimental factors and sample groups, and standardization of quantitative-result formats. Together, these developments connect raw-data preservation, standardized metadata, reproducible reanalysis, biological visualization, and cross-repository interoperability. Although further implementation and large-scale validation are required, they provide a practical foundation for integrating proteomic, metaproteomic, and metabolomic data in future trans-omics studies.
ER -