MRMhub
Reproducible, automated and scalable processing of targeted metabolomics and lipidomics data
MRMhub is an open-source, one-stop framework for reproducible, automated processing of targeted metabolomics and lipidomics data acquired by liquid chromatography–mass spectrometry (LC-MS) in multiple reaction monitoring (MRM) mode. Addressing well-known gaps in the robustness and scalability of existing software, it provides a reproducible, end-to-end workflow — from raw instrument data to quality-controlled quantitative results — at population scale on standard hardware, processing large studies within minutes while recording a full digital footprint of every step for reproducibility and traceability. Its modular functions and defined data structures adapt to diverse study designs and data formats, and support collaboration between analytical and bioinformatics scientists.
The MRMhub modules
Both are customizable and can be used together or independently:
- INTEGRATOR ↗ — a fast, memory-efficient standalone application for consensus-based peak integration of large-scale analyses, with per-feature integration settings. It reads mzML (vendor raw files converted via msconvert) and exports integrated peak areas that feed directly into QUANT or other post-processing tools.
- QUANT ↗ — a programmatic R library (
mrmhub) for building tailored, reproducible post-processing and quality-control pipelines. It reads INTEGRATOR results directly, or feature-intensity data from other sources (CSV, mzTab-M, Skyline).
Getting started
- Browse real analyses ↗ — annotated, end-to-end reports from large-scale studies.
- INTEGRATOR Quick Start ↗ (peak integration) and Getting started with QUANT ↗ (post-processing).
- Run the demo — the bundled demo project with data showcasing both modules.
Citation: Burla B. et al. (2025). MRMhub: one-stop solution for automated processing of large-scale targeted metabolomics data. bioRxiv. doi:10.64898/2025.12.20.695370 | Source: github.com/SLINGhub/MRMhub