Metabolomics Navigator Tools, strategies & workflow guidance for metabolomics

Preprocessing and feature extraction

Eclipse

Match corresponding features across untargeted LC-MS datasets.

LC-MSPython packageSource available with restrictions
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Overview

Eclipse is a BMXP Python module that aligns feature tables using retention time, m/z and intensity, then aggregates matches through a graph.

What can this tool do?

Retention-time alignment

Common uses

  • Match corresponding features across untargeted LC-MS datasets.

Scientific fit

Primary function

Preprocessing and feature extraction

Data compatibility

Inputs

Feature or peak table

Outputs

Feature or peak table, Human-readable report

Input formats

CSV or DataFrame tables with feature ID, RT, m/z and intensity

Output formats

Matched-feature CSV tables and alignment reports

Scope and considerations

Designed for

  • Eclipse is a BMXP Python module that aligns feature tables using retention time, m/z and intensity, then aggregates matches through a graph.

Not designed for

  • Raw-file peak detection or structural confirmation of aligned features.

Important requirements

  • Python with BMXP and extracted feature tables from compatible LC-MS methods.

Considerations

  • Inspect alignment diagnostics and thresholds. Different gradients require the documented prescaling; arbitrary methods are not automatically compatible.

Access and documentation

Primary accessDocumentation

The LICENSE is headed MIT License (Dual License) but adds a commercial-redistribution restriction. Recorded as source available, not standard MIT; consult the actual license for intended use.

Evidence and review

Enveda intake candidate checked against official documentation, license information and primary publication on 2026-10-21. Editorial review only; no execution or independent benchmark.

Core publications

Resource papers, direct updates and tool-specific methods. Selection policy.

  1. Eclipse : a Python package for alignment of two or more nontargeted LC-MS metabolomics datasets. Bioinformatics (2025). doi:10.1093/bioinformatics/btaf290

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Entry history

Changes to this catalogue entry, not the tool's software release history. Acceptance and editorial review are separate.

  1. 2026-10-21 · First committed entry

    Add nine reviewed Enveda tools and reconcile intake coverage

    View change · Entry at this revision

Full GitHub history