bio-metabolomics-xcms-preprocessing
XCMS3 workflow for LC-MS/MS metabolomics preprocessing. Covers peak detection, retention time alignment, correspondence (grouping), and gap filling. Use when processing raw LC-MS data into a feature table for untargeted metabolomics.
npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-metabolomics-xcms-preprocessing --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
## Version Compatibility Reference examples tested with: MSnbase 2.28+, scanpy 1.10+, xcms 4.0+ Before using code patterns, verify installed versions match. If versions differ: - R: `packageVersion('<pkg>')` then `?function_name` to verify parameters If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. # XCMS Metabolomics Preprocessing Requires Bioconductor 3.18+ with xcms 4.0+ and MSnbase 2.28+. ## Load Raw Data **Goal:** Import raw LC-MS files into R for downstream peak detection and alignment. **Approach:** Read mzML/mzXML files into an OnDiskMSnExp object using MSnbase for memory-efficient access. **"Process my raw LC-MS data into a feature table"** → Detect chromatographic peaks, align retention times across samples, group corresponding peaks, and fill missing values to produce a sample-by-feature intensity matrix. ```r library(xcms) library(MSnbase) # Read mzML/mzXML files raw_files <- list.files('raw_data', pattern = '\\.(mzML|mzXML)$', full.names = TRUE) # Create OnDiskMSnExp object raw_data <- readMSData(raw_files, mode = 'onDisk') # Check data raw_data table(msLevel(r
- Version Compatibility
- Load Raw Data
- Define Sample Groups
- Peak Detection (Centroided)
- Peak Detection (Profile Data)
- Retention Time Alignment
- Peak Correspondence (Grouping)
- Gap Filling
- Extract Feature Table
- Quality Control
- CAMERA Annotation (Isotopes/Adducts)
- Export for MetaboAnalyst
- Related Skills
What does the bio-metabolomics-xcms-preprocessing skill do?
XCMS3 workflow for LC-MS/MS metabolomics preprocessing. Covers peak detection, retention time alignment, correspondence (grouping), and gap filling. Use when processing raw LC-MS data into a feature table for untargeted metabolomics.
How do I install it?
Run `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-metabolomics-xcms-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.