MetabWatch

MetabWatch watches a folder of Thermo .raw files, matches QC compounds (or a peak list from the first matching sample), and refreshes an HTML dashboard.

Lab use is the MetabWatch window. Command line: docs/cli.md.

Open MetabWatch

Windows (recommended):

Double-click the desktop shortcut (named with the version, e.g. MetabWatch 0.3.0), or Start-MetabWatch.ps1 in the repo folder.

Or run metabwatch-gui from the command line within an appropriately configured Python environment.

Instructions for Windows installation: Windows install.

macOS (developers only):

Lab use is Windows. macOS is for developers only. Run metabwatch-gui from a configured Python environment. Setup: Maintainer / development (points at CoreMS for Thermo .raw / pythonnet).

Quick Start (from GUI)

1. Choose Preset Method — packaged HILIC or RP method.
2. Search — Targeted (packaged QC list) or Untargeted (peak list from the first matching sample).
3. Polarity — Auto (detects from first sample and locks in the rest), Positive, or Negative.
4. Project ID (optional) — only files whose name contains this text.
5. Input folder / Output folder.
6. Process once (what is already there) or Watch continuously (new files until Stop).
7. Start.
8. Open dashboard

What the options mean

• Targeted matches the method’s compound list. Untargeted builds a list from the first sample whose name matches the usual filter (QC_Metab_ or Pool).
• Polarity: Auto locks from the first successful file; Positive/Negative lock before the first sample. One polarity per output folder.
• Project ID: extra file-name filter. Leave empty to keep only the usual sample filter.
• Force reprocess: run again even if that file was already done.

Do not mix positive and negative into one output folder. If polarity is set up front, matching files in a mixed input folder still run. If polarity is Auto, a mixed batch stops after the first mismatch.

Custom compound list

Create custom config writes a new folder (metabwatch_config, or _2 if that name is taken) with JSON, a copy of CoreMS settings, a README.txt, and (targeted) a blank monitored_compounds.csv. Existing folders are not overwritten. Fill the CSV of monitored_compounds before a targeted Start for targeted runs. More details can be found in folder’s README.txt.

Results

• dashboard.html — compound table and plots (offline; no internet needed)
• compounds/ — one page per compound
• matches/ — per-sample match CSVs
• traces/ — per-sample MS1 traces and TIC plots
• export_mz.csv, export_rt.csv, export_height.csv, export_area.csv

More

• Windows install — lab PC, shortcut
• Command line — metabwatch flags and JSON
• Maintainer / development — Python, macOS, CoreMS
• Changelog