bio-metagenomics-metaphlan
Marker gene-based taxonomic profiling using MetaPhlAn 4. Provides accurate species-level relative abundances using clade-specific markers. Use when accurate taxonomic profiling is needed and computational resources are limited, or for comparison with HMP/other MetaPhlAn studies.
npx skills add BioTender-max/awesome-bio-agent-skills --skill metaphlan-profiling --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: Bowtie2 2.5.3+, MetaPhlAn 4.1+, minimap2 2.26+, pandas 2.2+, scanpy 1.10+ Before using code patterns, verify installed versions match. If versions differ: - Python: `pip show <package>` then `help(module.function)` to check signatures - 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. # MetaPhlAn 4 Profiling **"Profile the species composition of my metagenome"** → Determine species-level relative abundances from shotgun metagenomic reads using clade-specific marker gene alignment. - CLI: `metaphlan sample.fastq --input_type fastq -o profile.txt` MetaPhlAn 4 uses ~5M clade-specific markers from 26,970 species-level genome bins. Supports both short reads (bowtie2) and long reads (minimap2). ## Basic Profiling ```bash # Profile single sample metaphlan sample.fastq.gz \ --input_type fastq \ --output_file profile.txt ``` ## Paired-End Reads ```bash # MetaPhlAn processes PE as single file or concatenated metaphlan reads_R1.fastq.gz,reads_R2.fastq.gz \ --input_typ
- Version Compatibility
- Basic Profiling
- Paired-End Reads
- Save Mapping Output for Reuse
- Long-Read Support (MetaPhlAn 4+)
- Common Options
- Install Database
- Analysis Types
- Multiple Samples
- Filter by Taxonomic Level
- Output Format
- Parse Output in Python
- Extract SGBs (Strain-level)
- Sample Metadata in Output
Profile single sample metaphlan sample.fastq.gz \ MetaPhlAn processes PE as single file or concatenated metaphlan reads_R1.fastq.gz,reads_R2.fastq.gz \ First run - save intermediate mapping Rerun with different settings without realigning metaphlan sample.map.bz2 \ Long reads automatically use minimap2 instead of bowtie2 metaphlan long_reads.fastq.gz \ Download database (done automatically on first run)
What does the bio-metagenomics-metaphlan skill do?
Marker gene-based taxonomic profiling using MetaPhlAn 4. Provides accurate species-level relative abundances using clade-specific markers. Use when accurate taxonomic profiling is needed and computational resources are limited, or for comparison with HMP/other MetaPhlAn studies.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill metaphlan-profiling --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 BioTender-max/awesome-bio-agent-skills, a repository with 135 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.