bio-metabolomics-statistical-analysis
Statistical analysis for metabolomics data. Covers univariate testing, multivariate methods (PCA, PLS-DA), and biomarker discovery. Use when identifying differentially abundant metabolites or building classification models.
npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-metabolomics-statistical-analysis --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: R stats (base), ggplot2 3.5+ 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. # Metabolomics Statistical Analysis ## Univariate Analysis **Goal:** Identify differentially abundant metabolites between experimental groups using feature-wise statistical tests. **Approach:** Apply t-tests to each feature independently, then correct for multiple testing with Benjamini-Hochberg FDR. **"Find the differentially abundant metabolites between my groups"** → Apply univariate and multivariate statistical methods to identify metabolites with significant abundance differences. ```r library(tidyverse) # Load normalized data data <- read.csv('normalized_data.csv', row.names = 1) groups <- factor(read.csv('sample_info.csv')$group) # T-test for each feature ttest_results <- apply(data, 2, function(x) { test <- t.test(x ~ groups) c(pvalue = test$p.value, fc = mean(x[groups == levels(gr
- Version Compatibility
- Univariate Analysis
- Fold Change Calculation
- Volcano Plot
- PCA
- PLS-DA
- sPLS-DA (Sparse)
- OPLS-DA (Orthogonal PLS-DA)
- Random Forest
- ROC Analysis
- Heatmap
- Related Skills
What does the bio-metabolomics-statistical-analysis skill do?
Statistical analysis for metabolomics data. Covers univariate testing, multivariate methods (PCA, PLS-DA), and biomarker discovery. Use when identifying differentially abundant metabolites or building classification models.
How do I install it?
Run `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-metabolomics-statistical-analysis --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.