Integrating Proteoform and Targeted Proteomics Data for Multi-Layer Protein Characterization

[ryanlamers]

Title

Integrating Proteoform and Targeted Proteomics Data for Multi-Layer Protein Characterization

Abstract

Mass spectrometry-based proteomics and targeted affinity platforms such as Olink provide complementary views of protein biology. Mass spectrometry enables the identification of proteoforms and post-translational modifications (PTMs), while Olink provides robust, high-throughput protein abundance measurements across large clinical cohorts. However, these data types are typically analyzed independently, limiting connections between protein abundance, molecular diversity, and functional regulation.

This project aims to develop computational approaches that integrate mass spectrometry-derived proteoform and PTM information with Olink protein abundance measurements. Rather than merging quantitative values onto a common scale, the hackathon will focus on strategies to link and jointly interpret these datasets. Approaches may include mapping Olink measurements to corresponding proteoforms or PTMs, identifying associations between protein abundance and modification states, and generating biologically interpretable outputs for downstream statistical analysis and visualization.

The resulting framework will establish standardized methods for harmonizing complementary proteomics datasets, helping distinguish changes in total protein abundance from alterations in specific proteoforms or modification states. This approach could improve biological interpretation, facilitate biomarker discovery, and provide a scalable foundation for integrating targeted and discovery proteomics data across clinical and translational research applications.

Project Plan

During the Hackathon, we aim to:

• Explore innovative approaches to connect and compare mass spectrometry proteoform/PTM data with Olink protein measurements across platforms, with the goal of identifying meaningful relationships, complementary insights, and future opportunities for data integration.
• Create protein- and proteoform-level mapping strategies using shared protein identifiers and annotation resources.
• Design/prototype data structures and software modules for integrated quantitative analysis.
• Demonstrate the workflow using representative datasets and generate proof-of-concept visualizations highlighting concordant and discordant protein-level changes.

After the Hackathon, we will:

• Expand support for additional targeted proteomics and affinity-based platforms.
• Incorporate biological pathway and PTM annotation databases to improve interpretation.
• Validate the framework using larger clinical cohorts and publicly available datasets.
• Release the workflow as an open-source package with reproducible documentation and example datasets.

Technical Details

Programming language: Python and R, among others.

Will build on existing software: pyOpenMS/OpenMS, Bioconductor/CRAN packages, OlinkAnalyze (or equivalent Olink analysis tools), Scanpy/AnnData (where applicable). For participants interested in the AnnData/APB workflow, please also refer to “Quality control of biological plasma samples and their MS or Olink measurements with APB”
#14.

Datasets: Mass spectrometry proteoform/PTM datasets and matched Olink targeted proteomics measurements from publicly available or consortium-provided benchmark datasets.

Prerequisites: If you are not familiar with Olink data, please download the Olink Analyze script package and familiarize yourself with the data format using some of the scripts and example datasets provided in Olink Analyze: https://cran.r-project.org/web/packages/OlinkAnalyze/index.html.

Contact information

Klev Diamanti
Senior Data Scientist
Olink Proteomics, part of Thermo Fisher Scientific
klev.diamanti@olink.com]

Marianne Sandin,
Senior Data Scientist
Olink Proteomics, part of Thermo Fisher Scientific
marianne.sandin@olink.com