BI
Data & Repro
bio-metabolomics-lipidomics
Specialized lipidomics analysis for lipid identification, quantification, and pathway interpretation. Covers LC-MS lipidomics with LipidSear…
FreedomIntelligence/OpenClaw-Medical-SkillsView
Data & Repro
BI
bio-metabolomics-targeted-analysis
Maintainer FreedomIntelligence · Last updated April 1, 2026
Targeted metabolomics analysis using MRM/SRM with standard curves. Covers absolute quantification, method validation, and quality assessment. Use when quantifying specific metabolites using calibration curves and internal standards.
Original source
FreedomIntelligence/OpenClaw-Medical-Skills
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-metabolomics-targeted-analysis
- Maintainer
- FreedomIntelligence
- License
- MIT
- Last updated
- April 1, 2026
Skill Snapshot
Key Details From SKILL.md
Key Notes
- CLI: Skyline for peak integration and export.
- Python/R: calibration curve fitting and sample quantification.
- Quantify specific metabolites from my MRM data" → Perform absolute quantification using calibration curves, internal standards, and quality assessment for targeted metabolomics. CLI: Skyline for peak integration and export Python/R: calibration curve fitting and sample quantification.
- skyline_data <- read.csv('skyline_export.csv').
Source Doc
Excerpt From SKILL.md
Filter to quantifier transitions
quant_data <- skyline_data %>% filter(Quantitative == TRUE | is.na(Quantitative))
Pivot to matrix format
intensity_matrix <- quant_data %>% select(Replicate, Molecule, Area) %>% pivot_wider(names_from = Replicate, values_from = Area)
## Standard curve data
standards <- data.frame(
concentration = c(0, 1, 5, 10, 50, 100, 500, 1000), # nM
area = c(100, 5000, 25000, 50000, 240000, 480000, 2300000, 4500000)
)
Use cases
- Use when quantifying specific metabolites using calibration curves and internal standards.
Not for
- Do not rely on this catalog entry alone for installation or maintenance details.
Upstream Related Skills
- xcms-preprocessing - Peak detection for targeted features
- normalization-qc - QC-based normalization
- statistical-analysis - Group comparisons
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