bio-microbiome-differential-abundance
Differential abundance testing for microbiome data using compositionally-aware methods like ALDEx2, ANCOM-BC2, and MaAsLin2. Use when identifying taxa that differ between experimental groups while accounting for the compositional nature of microbiome data.
npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-microbiome-differential-abundance --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: DESeq2 1.42+, ggplot2 3.5+, phyloseq 1.46+, scanpy 1.10+ 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. # Differential Abundance Testing **"Find which taxa differ between my groups"** → Identify differentially abundant taxa between experimental conditions using compositionally-aware methods that account for the relative nature of microbiome data. - R: `ALDEx2::aldex()` for CLR-transformed Welch's t-test - R: `ANCOMBC::ancombc2()` for bias-corrected log-linear models - R: `Maaslin2::Maaslin2()` for multivariable association ## The Compositionality Problem Microbiome data is compositional - abundances are relative, not absolute. Standard tests (t-test, DESeq2) can give false positives. ## ALDEx2 (Recommended) **Goal:** Identify differentially abundant taxa between groups using a compositionally-aware statistical framework. **Approach:** Apply CLR transformation with
- Version Compatibility
- The Compositionality Problem
- ALDEx2 (Recommended)
- ANCOM-BC2 (Recommended)
- MaAsLin2
- DESeq2 (with caution)
- Visualization
- Method Comparison
- Related Skills
What does the bio-microbiome-differential-abundance skill do?
Differential abundance testing for microbiome data using compositionally-aware methods like ALDEx2, ANCOM-BC2, and MaAsLin2. Use when identifying taxa that differ between experimental groups while accounting for the compositional nature of microbiome data.
How do I install it?
Run `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-microbiome-differential-abundance --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.