MetabolitProfiler

MetabolitProfiler is a software platform designed for metabolomics data analysis that enables researchers to profile, identify, and quantify metabolites across biological samples. It supports end-to-end workflows from raw spectrometric or nuclear magnetic resonance data to a consolidated, quantifiable metabolite matrix suitable for downstream statistical analysis and pathway interpretation.

Its core features include data import from liquid chromatography–mass spectrometry (LC-MS), gas chromatography–mass spectrometry (GC-MS), and NMR experiments; peak detection and deconvolution; retention-time alignment and feature grouping across samples; spectral library matching for metabolite identification using public and in-house databases; annotation with chemical identifiers such as InChI and SMILES; isotopologue analysis and labeling support; flexible quantification workflows (absolute or relative); quality control metrics and batch-effect assessment; and export of results in standard formats with compatibility for downstream statistical and visualization tools.

MetabolitProfiler emphasizes interoperability and reproducibility. It adheres to open data standards such as mzML, mzXML, nmrML, and mzTab, and offers a modular architecture that can run as a desktop application or server-based service. The platform supports scripting and workflow automation, audit trails, and containerized deployment to facilitate reproducible analyses across computing environments. It also integrates with pathway databases like KEGG and Reactome for enrichment analysis and contextual interpretation.

Applications span clinical metabolomics, plant and microbial metabolomics, environmental metabolomics, and nutrition research, where researchers seek biomarker discovery, mechanistic insights, and cross-species comparisons. As a general-purpose tool, MetabolitProfiler reflects common capabilities found in contemporary metabolomics software while allowing extensibility through plug-ins and custom modules.