Alphagenome Single Variant Analysis
google-deepmind/science-skills
Analyzes genetic variant effects on gene expression (RNA-seq), chromatin accessibility (DNASE), histone marks (ChIP), and transcription factors using the AlphaGenome API.
Resolves and compares bacterial strains below the species level from shotgun metagenomes with inStrain (popANI/conANI microdiversity), StrainPhlAn (marker-SNV consensus phylogeny and nGD), MIDAS2…
$ npx skills add GPTomics/bioSkills --skill bio-metagenomics-strain-tracking -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install GPTomics/bioSkills bio-metagenomics-strain-tracking --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/GPTomics/bioSkills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/metagenomics/strain-tracking .claude/skills/bio-metagenomics-strain-tracking && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "bio-metagenomics-strain-tracking" agent skill from https://github.com/GPTomics/bioSkills/tree/main/metagenomics/strain-tracking into .claude/skills/bio-metagenomics-strain-tracking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bio-metagenomics-strain-tracking", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/GPTomics/bioSkills/tree/main/metagenomics/strain-trackingType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add GPTomics/bioSkills --skill bio-metagenomics-strain-tracking -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install GPTomics/bioSkills bio-metagenomics-strain-tracking --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/GPTomics/bioSkills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/metagenomics/strain-tracking .agents/skills/bio-metagenomics-strain-tracking && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "bio-metagenomics-strain-tracking" agent skill from https://github.com/GPTomics/bioSkills/tree/main/metagenomics/strain-tracking into .agents/skills/bio-metagenomics-strain-tracking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bio-metagenomics-strain-tracking", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add GPTomics/bioSkills --skill bio-metagenomics-strain-tracking -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install GPTomics/bioSkills bio-metagenomics-strain-tracking --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/GPTomics/bioSkills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/metagenomics/strain-tracking .cursor/skills/bio-metagenomics-strain-tracking && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "bio-metagenomics-strain-tracking" agent skill from https://github.com/GPTomics/bioSkills/tree/main/metagenomics/strain-tracking into .cursor/skills/bio-metagenomics-strain-tracking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bio-metagenomics-strain-tracking", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/GPTomics/bioSkills.git --path metagenomics/strain-tracking--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add GPTomics/bioSkills --skill bio-metagenomics-strain-tracking -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install GPTomics/bioSkills bio-metagenomics-strain-tracking --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/GPTomics/bioSkills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/metagenomics/strain-tracking .gemini/skills/bio-metagenomics-strain-tracking && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "bio-metagenomics-strain-tracking" agent skill from https://github.com/GPTomics/bioSkills/tree/main/metagenomics/strain-tracking into .gemini/skills/bio-metagenomics-strain-tracking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bio-metagenomics-strain-tracking", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install GPTomics/bioSkills bio-metagenomics-strain-trackingInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add GPTomics/bioSkills --skill bio-metagenomics-strain-tracking -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/GPTomics/bioSkills.git skills-src && mkdir -p .github/skills && cp -r skills-src/metagenomics/strain-tracking .github/skills/bio-metagenomics-strain-tracking && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "bio-metagenomics-strain-tracking" agent skill from https://github.com/GPTomics/bioSkills/tree/main/metagenomics/strain-tracking into .github/skills/bio-metagenomics-strain-tracking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bio-metagenomics-strain-tracking", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add GPTomics/bioSkills --skill bio-metagenomics-strain-tracking -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install GPTomics/bioSkills bio-metagenomics-strain-tracking --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/GPTomics/bioSkills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/metagenomics/strain-tracking .opencode/skills/bio-metagenomics-strain-tracking && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "bio-metagenomics-strain-tracking" agent skill from https://github.com/GPTomics/bioSkills/tree/main/metagenomics/strain-tracking into .opencode/skills/bio-metagenomics-strain-tracking/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bio-metagenomics-strain-tracking", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
bio-metagenomics-strain-trackingResolves and compares bacterial strains below the species level from shotgun metagenomes with inStrain (popANI/conANI microdiversity), StrainPhlAn (marker-SNV consensus phylogeny and nGD), MIDAS2…
Bio Metagenomics Strain Tracking is an agent skill from GPTomics/bioSkills. Resolves and compares bacterial strains below the species level from shotgun metagenomes with inStrain (popANI/conANI microdiversity), StrainPhlAn (marker-SNV consensus phylogeny and nGD), MIDAS2, metaSNV, and StrainGE, plus genome-vs-genome ANI (skani/fastANI/MASH) for isolate/MAG comparison. Covers why a strain is a threshold not a thing, why ANI answers same-genome while popANI/nGD answer same-population-in-situ, the 99.999% popANI and per-species nGD definitions, the coverage detection limit (absence is not…
Its SKILL.md is about 3.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files (for example `examples/instrain_workflow.sh`, `examples/mash_comparison.sh` and `examples/parse_instrain_compare.py`).
It sits in Research & Science, covering Bioinformatics. The repository describes itself as: a set of SKILLS.md for doing bioinformatics with agents like claude code. The licence is MIT.
2 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit d91ed3d. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Ships script files (Shell and Python), which the agent can run.
Shell commands in SKILL.md call:
pipFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use pip, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Bio Metagenomics Strain Tracking loads about 3.7k tokens when it runs. Until then it costs about 229 tokens; SKILL.md has 1,593 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from GPTomics/bioSkills at commit d91ed3d, republished under its MIT licence (© GPTomics). 1,593 words, ~3,679 tokens.
.claude/skills/bio-metagenomics-strain-tracking/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.Reference examples tested with: inStrain 1.8+, StrainPhlAn/MetaPhlAn 4.1+, dRep 3.4+, skani 0.2+, Bowtie2 2.5+, samtools 1.19+, pandas 2.2+.
Before using code patterns, verify installed versions match. If versions differ:
inStrain profile -h, strainphlan -h, skani dist -h to confirm flags and defaultspip show <package> then help(module.function) to check signaturesIf code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.
The mapping REFERENCE defines the answer. Map to genomes present in the sample set (dRep-dereplicated MAGs from this dataset), not generic database genomes - a distant reference inflates apparent SNVs and corrupts popANI. Record the reference set, the popANI/nGD threshold, the minimum coverage and breadth, and the co-detection rate; the "strain" is defined by these, not by nature.
"Is the same strain in samples A and B?" -> Compare per-position SNV populations (not consensus genomes) at adequate depth - because a strain is defined by the chosen threshold, and ANI cannot resolve the difference that matters.
inStrain profile sample.bam reps.fasta -o sample.IS -s reps.stb -p 8 then inStrain compareScope: in-situ strain resolution, sharing, and deconvolution from a community. Pure-culture isolate outbreak SNP/cgMLST trees -> epidemiological-genomics. MAG assembly/binning -> genome-assembly/metagenome-assembly. Species presence/abundance -> kraken-classification, metaphlan-profiling.
There is no universal definition of a metagenomic strain. A strain is an operational construct fixed by the reference mapped to, the genome fraction comparable at adequate depth, and the cutoff drawn. inStrain's popANI >= 99.999% over >= 50% of the genome IS the strain definition; Valles-Colomer's per-species nGD threshold IS the strain definition. Changing the cutoff changes how many strains exist. Two corollaries:
| Task | Question | Tools |
|---|---|---|
| Identification | which known reference strain is present? | StrainGST, sourmash gather, MIDAS |
| Tracking / sharing | is the SAME strain in samples A and B? | inStrain compare, StrainPhlAn, MIDAS2, metaSNV, SameStr |
| Deconvolution | how many strains coexist in ONE sample, what are their haplotypes? | DESMAN, Strainberry, strainFlye, Strainy |
Genome-to-genome ANI (MASH/skani/fastANI) is a fourth, orthogonal task - "are these two assembled genomes the same?" - isolate/MAG comparison and dereplication, NOT in-situ strain resolution.
| Tool | Citation | Mechanism / role | When |
|---|---|---|---|
| inStrain | Olm 2021 Nat Biotechnol 39:727 | popANI/conANI microdiversity from reads mapped to MAGs | the reference standard for shared-strain detection |
| StrainPhlAn | Truong 2017 Genome Res 27:626 | marker-SNV consensus -> phylogeny -> nGD | large cross-sample marker surveys, no assembly needed |
| MIDAS2 | Zhao 2023 Bioinformatics 39:btac713 | UHGG pan-genome SNV + gene CNV | accessory-genome strain signal at scale |
| StrainGE | van Dijk 2022 Genome Biol 23:74 | k-mer search + low-coverage variant calling | low-abundance strains down to 0.5x coverage |
| metaSNV v2 | Van Rossum 2022 Bioinformatics 38:1162 | SNV distances + subspecies clustering | subspecies structure across samples |
| skani | Shaw 2023 Nat Methods 20:1661 | sparse-chaining ANI | genome-vs-genome ANI; robust on fragmented MAGs (prefer over fastANI) |
| Strainberry / strainFlye | Vicedomini 2021 Nat Commun 12:4485; Fedarko 2022 Genome Res 32:2119 | long-read haplotype separation | deconvolute co-occurring strains (-> genome-assembly) |
| Scenario | Recommended | Why |
|---|---|---|
| Is a strain shared between two metagenomes? | inStrain compare (popANI) | microdiversity-aware; the field standard |
| Cross-sample transmission survey, many samples | StrainPhlAn (per-species nGD) | marker-based, scalable, no assembly |
| Low-abundance pathogen (< 1% / < 5x) | StrainGE | detects/compares down to 0.5x |
| Accessory-genome / pan-genome strain signal | MIDAS2 | adds gene-content axis SNV tools miss |
| Separate co-occurring strains into haplotypes | DESMAN (many samples) or long-read Strainberry/strainFlye | SNV tools do not partition a mixture |
| Compare two assembled genomes / dereplicate | skani (or fastANI) | genome-vs-genome ANI, not in-situ strains |
| Pure-culture isolate outbreak tree | -> epidemiological-genomics | cgMLST/SNP-distance on one genome per sample |
Goal: Decide whether two metagenomes share a strain without being fooled by which allele happens to be the majority.
Approach: dRep the dataset's MAGs into representative genomes, map reads to the concatenated references, profile each sample, then compare on popANI (microdiversity-aware) over the co-covered genome fraction.
# 1. dRep -> representative genomes (97-99% ANI); concatenate; build scaffold-to-bin (.stb).
# 2. Map reads to the concatenated reps - your OWN MAGs, not database genomes.
bowtie2 -x reps -1 r1.fq.gz -2 r2.fq.gz | samtools sort -o sampleA.bam
inStrain profile sampleA.bam reps.fasta -o sampleA.IS -s reps.stb -g genes.fna -p 8
inStrain profile sampleB.bam reps.fasta -o sampleB.IS -s reps.stb -g genes.fna -p 8
inStrain compare -i sampleA.IS sampleB.IS -o compare.out -s reps.stb -p 8conANI calls a difference whenever the consensus base differs - confounded by within-sample microdiversity (a minor-allele flip fakes a difference). popANI calls a difference only if the two samples share NO alleles at all, including minor ones, so popANI >= conANI always and is what detects shared strains consensus tools miss. Read genome-level calls from genomeWide_compare.tsv (breadth column percent_compared); the per-scaffold comparisonsTable.tsv uses percent_genome_compared.
metaphlan sample.fq.gz --input_type fastq -s sample.sam.bz2 --bowtie2out sample.bz2 -o profile.tsv # need the SAM (-s)
sample2markers.py -i sams/*.sam.bz2 -o consensus_markers -n 8
extract_markers.py -c t__SGB1877 -o clade_markers/
strainphlan -s consensus_markers/*.json -m clade_markers/t__SGB1877.fna \
-r reference_genomes/*.fna.bz2 -o output -c t__SGB1877 \
--marker_in_n_samples_perc 80 --sample_with_n_markers 20 --nproc 8 # 4.0 named this --marker_in_n_samplesThe output tree gives a pairwise nGD (normalized genetic distance). There is no universal nGD strain cutoff - derive a per-species threshold from the data (same-individual-different-timepoint pairs fall below it, unrelated pairs above), as in Valles-Colomer 2023. Low coverage means too few markers pass the filters and the sample is dropped from the species tree silently - so a missing shared-strain call is not evidence of no shared strain.
skani dist genomeA.fasta genomeB.fasta # prefer skani over fastANI: robust on fragmented MAGs~95% ANI is the species boundary (Jain 2018 Nat Commun 9:5114). ANI saturates above that and cannot resolve same-vs-different strain - use it to compare isolates/MAGs and to dereplicate, never to call transmission.
Trigger: "MASH distance < 0.001 = same strain" or "fastANI > 99% = same strain." Mechanism: ANI operates on consensus genomes, saturates above 99.9%, and ignores microdiversity. Symptom: distinct transmissible strains called identical; transmission inferred from an ANI number. Fix: use ANI for isolate/MAG comparison; use inStrain popANI / StrainPhlAn nGD for strain sharing.
Trigger: concluding "no transmission" or "strain turnover." Mechanism: a shared strain can only be called for a species detected at adequate depth in BOTH samples (inStrain >= 5x and >= 50% breadth; StrainPhlAn enough markers). Symptom: a coverage dropout misread as biological absence; sharing rates biased to abundant taxa. Fix: report co-detection rates alongside sharing rates; use StrainGE for low-abundance targets.
Trigger: narrating "A infected B." Mechanism: a shared strain is an undirected edge. Symptom: directionality claimed from one cross-sectional comparison. Fix: direction comes from timepoints, contact metadata, or a known index case - the published landscapes infer it from study design, not the genomic comparison.
Trigger: mapping to a generic database genome. Mechanism: a distant reference inflates apparent SNVs. Symptom: corrupted popANI; spurious differences. Fix: map to dRep-dereplicated MAGs from the sample set.
Trigger: "what are the two strains here?" from inStrain. Mechanism: SNV/marker tools characterize population diversity; they do not partition it into haplotypes. Symptom: a category error. Fix: use DESMAN (many samples) or long-read Strainberry/strainFlye/Strainy for haplotype separation.
| Threshold | Source | Rationale |
|---|---|---|
| popANI >= 99.999% same strain | Olm 2021 Nat Biotechnol 39:727 | empirical shared-strain cutoff; IS the operational definition |
| percent_compared >= 50% (genome-level breadth) | Olm 2021 Nat Biotechnol 39:727 | a genome below 50% breadth is not confidently present |
| min_cov 5x | Olm 2021 Nat Biotechnol 39:727 | lowest coverage at which sub-50% minor alleles are reliable |
| StrainGE detection ~0.5x | van Dijk 2022 Genome Biol 23:74 | tracks low-abundance strains below the inStrain floor |
| Per-species nGD threshold (derive it) | Valles-Colomer 2023 Nature 614:125 | no universal cutoff; separate within-host timepoints from unrelated |
| ~95% ANI species boundary | Jain 2018 Nat Commun 9:5114 | ANI saturates above this; cannot resolve strains |
| Error / symptom | Cause | Solution |
|---|---|---|
| Everything looks like one strain | ANI/MASH used for strain calls | switch to inStrain popANI / StrainPhlAn nGD |
| Sample missing from the StrainPhlAn tree | too few markers passed filters at low coverage | report co-detection; do not read absence as no-sharing |
| popANI implausibly low across the board | mapped to a distant database reference | map to dRep MAGs from the dataset |
| inStrain compare gives no genomes | < 50% breadth or < 5x in one sample | deepen sequencing or use StrainGE for that taxon |
| "Who infected whom" asked of one timepoint | sharing is undirected | need longitudinal/epi design for direction |
© GPTomics, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 4 other files in metagenomics/strain-tracking of GPTomics/bioSkills.
Open the folder on GitHubat commit d91ed3d
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in GPTomics/bioSkills, which our catalogue first saw on October 7, 2026.
Bio Metagenomics Strain Tracking next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Bio Metagenomics Strain Tracking this skillGPTomics/bioSkills | 1.2k | 1 repos | ~3.7k | Automated safety check: Pass | MIT | |
| Alphagenome Single Variant Analysisgoogle-deepmind/science-skills | 3.2k | 2 repos | ~3k | Automated safety check: Notes | Apache-2.0 | |
| 13C Metabolic Flux AnalysisK-Dense-AI/scientific-agent-skills | 48k | 1 repos | ~3.2k | Automated safety check: Pass | MIT | |
| Clinvar Databasegoogle-deepmind/science-skills | 3.2k | 2 repos | ~3.9k | Automated safety check: Notes | Apache-2.0 | |
| Metabolic Study Planneraiming-lab/AutoResearchClaw | 15k | — | ~1.9k | Automated safety check: Pass | MIT | |
| Dbsnp Databasegoogle-deepmind/science-skills | 3.2k | 2 repos | ~3.4k | Automated safety check: Notes | Apache-2.0 |
google-deepmind/science-skills
Analyzes genetic variant effects on gene expression (RNA-seq), chromatin accessibility (DNASE), histone marks (ChIP), and transcription factors using the AlphaGenome API.
K-Dense-AI/scientific-agent-skills
Estimates reaction fluxes inside cells from steady-state carbon-13 labeling data with a bundled mfapy-based solver, and reports which fluxes the data pin down.
google-deepmind/science-skills
A skill your agent uses when needing clinical significance, pathogenicity classifications (e.g., Pathogenic, Benign, VUS), clinical evidence rationales, or finding "hard positive" benchmark controls…
aiming-lab/AutoResearchClaw
Turns a broad metabolic modelling topic into a concrete, paper-shaped plan with organism, model, perturbations, metrics and figures before any FBA code is written.
google-deepmind/science-skills
A skill your agent uses when you want to look up, map, and search for short genetic variants (SNPs, indels) in NCBI's dbSNP database.
aiming-lab/AutoResearchClaw
Runs a metabolic flux analysis from model loading to phenotype prediction and figures by handing work to four sub-agents in sequence.
GPTomics/bioSkills
Read, write, and convert multiple sequence alignment files using Biopython Bio.AlignIO.
GPTomics/bioSkills
Installs the bioSkills collection of 425 bioinformatics skills in one step, or only chosen categories, so sequencing, RNA-seq, single-cell and variant tasks get specialized help.
GPTomics/bioSkills
Write biological sequences to files (FASTA, FASTQ, GenBank, EMBL) using Biopython Bio.SeqIO.
GPTomics/bioSkills
Soft- or hard-clips PCR primer footprints from aligned amplicon BAMs so primer bases stop masquerading as confirmed reference sequence.
GPTomics/bioSkills
Filters BAM alignments by FLAG bits, mapping quality and regions with samtools view or pysam, with recipes for common keep and drop cases.
GPTomics/bioSkills
Create and use BAI/CSI indices for BAM/CRAM files using samtools and pysam.
Categories
Resolves and compares bacterial strains below the species level from shotgun metagenomes with inStrain (popANI/conANI microdiversity), StrainPhlAn (marker-SNV consensus phylogeny and nGD), MIDAS2…. Bio Metagenomics Strain Tracking is an agent skill from GPTomics/bioSkills. Resolves and compares bacterial strains below the species level from shotgun metagenomes with inStrain (popANI/conANI microdiversity), StrainPhlAn (marker-SNV consensus phylogeny and nGD), MIDAS2, metaSNV, and StrainGE, plus genome-vs-genome ANI (skani/fastANI/MASH) for isolate/MAG comparison.
Bio Metagenomics Strain Tracking fits situations like: detecting shared strains; tracking transmission; resolving within-host strain dynamics; deconvoluting co-occurring strains.
Run `npx skills add GPTomics/bioSkills --skill bio-metagenomics-strain-tracking -a claude-code`. Or copy the skill folder (metagenomics/strain-tracking in GPTomics/bioSkills) into .claude/skills/bio-metagenomics-strain-tracking in your project. Claude Code loads it when a task matches its description.
Run `npx skills add GPTomics/bioSkills --skill bio-metagenomics-strain-tracking -a codex`. Or copy the skill folder (metagenomics/strain-tracking in GPTomics/bioSkills) into .agents/skills/bio-metagenomics-strain-tracking in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add GPTomics/bioSkills --skill bio-metagenomics-strain-tracking -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/bio-metagenomics-strain-tracking, .gemini/skills/bio-metagenomics-strain-tracking, .github/skills/bio-metagenomics-strain-tracking and .opencode/skills/bio-metagenomics-strain-tracking in your project.
Going by SKILL.md and its folder, Bio Metagenomics Strain Tracking needs a shell and Python for the scripts in its folder and the command-line tools its instructions call (pip). Our summary lists: Python 3; A Bash shell.
SKILL.md contains no URLs. Its commands use pip, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Bio Metagenomics Strain Tracking is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.7k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Bio Metagenomics Strain Tracking: Alphagenome Single Variant Analysis (google-deepmind/science-skills, 3.2k stars), 13C Metabolic Flux Analysis (K-Dense-AI/scientific-agent-skills, 48k stars), Clinvar Database (google-deepmind/science-skills, 3.2k stars) and Metabolic Study Planner (aiming-lab/AutoResearchClaw, 15k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
GPTomics (a GitHub organization) maintains it in GPTomics/bioSkills, which has 1,218 GitHub stars. The repository holds 559 skills in this directory. The repository was last updated on August 15, 2026.
Source: GPTomics/bioSkills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.