Agent skill

bio-metabolomics-msdial-preprocessing

MS-DIAL-based metabolomics preprocessing as alternative to XCMS. Covers peak detection, alignment, annotation, and export for downstream analysis. Use when processing MS-DIAL output files for R/Python analysis or when preferring GUI-based preprocessing.

FreedomIntelligencegithub.com/FreedomIntelligenceGitHub ↗
claude-code
Install
npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-metabolomics-msdial-preprocessing --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 3
SKILL.md size: 9 KB
Bundled scripts: none
Path: skills/bio-metabolomics-msdial-preprocessing/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 2,909
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

## Version Compatibility Reference examples tested with: numpy 1.26+, pandas 2.2+, scanpy 1.10+, xcms 4.0+ Before using code patterns, verify installed versions match. If versions differ: - Python: `pip show <package>` then `help(module.function)` to check signatures - R: `packageVersion('<pkg>')` then `?function_name` to verify parameters - CLI: `<tool> --version` then `<tool> --help` to confirm flags If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. # MS-DIAL Preprocessing **"Process my LC-MS data with MS-DIAL"** → Detect chromatographic peaks, align across samples, annotate metabolites, and export a feature table for statistical analysis. - CLI: MS-DIAL GUI or console mode for peak picking and alignment ## MS-DIAL GUI Workflow MS-DIAL provides a user-friendly GUI for complete metabolomics preprocessing: 1. **Project Setup** - Create new project, select data type 2. **Data Import** - Load mzML/ABF files 3. **Peak Detection** - Automatic peak picking 4. **Alignment** - Cross-sample alignment 5. **Gap Filling** - Fill missing values 6. **Annotation** - Database matching 7. *

What's inside
Steps it walks through
  1. Version Compatibility
  2. MS-DIAL GUI Workflow
  3. Export MS-DIAL Results to R
  4. Filter MS-DIAL Results
  5. MS-DIAL Data to XCMS-Like Format
  6. MS-DIAL Batch Processing (Console Mode)
  7. Parameter File Example
  8. Python Processing of MS-DIAL Output
  9. MS-DIAL Annotation Levels
  10. Compare MS-DIAL vs XCMS Results
  11. Export for MetaboAnalyst
  12. Normalization Options
  13. Related Skills
Ships with 2 files
  • examples/process_msdial_output.R
  • usage-guide.md
Commands it runs
MS-DIAL console application for batch processing
Available on Windows
Create parameter file (msdial_param.txt)
See MS-DIAL documentation for all parameters
Run MS-DIAL console
MsdialConsoleApp.exe lcmsdda -i input_folder -o output_folder -m msdial_param.txt
More from OpenClaw-Medical-Skills
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About this skill
What does the bio-metabolomics-msdial-preprocessing skill do?

MS-DIAL-based metabolomics preprocessing as alternative to XCMS. Covers peak detection, alignment, annotation, and export for downstream analysis. Use when processing MS-DIAL output files for R/Python analysis or when preferring GUI-based preprocessing.

How do I install it?

Run `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-metabolomics-msdial-preprocessing --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From FreedomIntelligence/OpenClaw-Medical-Skills, a repository with 2,909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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