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.
Phases small variants, SVs, and methylation from Oxford Nanopore and PacBio long reads (read-backed/physical phasing) with WhatsHap, LongPhase, or HiPhase, and haplotags the BAM (HP/PS tags) for…
$ npx skills add GPTomics/bioSkills --skill bio-long-read-sequencing-haplotype-phasing -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install GPTomics/bioSkills bio-long-read-sequencing-haplotype-phasing --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/long-read-sequencing/haplotype-phasing .claude/skills/bio-long-read-sequencing-haplotype-phasing && 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-long-read-sequencing-haplotype-phasing" agent skill from https://github.com/GPTomics/bioSkills/tree/main/long-read-sequencing/haplotype-phasing into .claude/skills/bio-long-read-sequencing-haplotype-phasing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bio-long-read-sequencing-haplotype-phasing", 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/long-read-sequencing/haplotype-phasingType 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-long-read-sequencing-haplotype-phasing -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install GPTomics/bioSkills bio-long-read-sequencing-haplotype-phasing --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/long-read-sequencing/haplotype-phasing .agents/skills/bio-long-read-sequencing-haplotype-phasing && 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-long-read-sequencing-haplotype-phasing" agent skill from https://github.com/GPTomics/bioSkills/tree/main/long-read-sequencing/haplotype-phasing into .agents/skills/bio-long-read-sequencing-haplotype-phasing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bio-long-read-sequencing-haplotype-phasing", 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-long-read-sequencing-haplotype-phasing -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install GPTomics/bioSkills bio-long-read-sequencing-haplotype-phasing --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/long-read-sequencing/haplotype-phasing .cursor/skills/bio-long-read-sequencing-haplotype-phasing && 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-long-read-sequencing-haplotype-phasing" agent skill from https://github.com/GPTomics/bioSkills/tree/main/long-read-sequencing/haplotype-phasing into .cursor/skills/bio-long-read-sequencing-haplotype-phasing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bio-long-read-sequencing-haplotype-phasing", 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 long-read-sequencing/haplotype-phasing--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-long-read-sequencing-haplotype-phasing -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install GPTomics/bioSkills bio-long-read-sequencing-haplotype-phasing --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/long-read-sequencing/haplotype-phasing .gemini/skills/bio-long-read-sequencing-haplotype-phasing && 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-long-read-sequencing-haplotype-phasing" agent skill from https://github.com/GPTomics/bioSkills/tree/main/long-read-sequencing/haplotype-phasing into .gemini/skills/bio-long-read-sequencing-haplotype-phasing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bio-long-read-sequencing-haplotype-phasing", 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-long-read-sequencing-haplotype-phasingInstalls 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-long-read-sequencing-haplotype-phasing -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/long-read-sequencing/haplotype-phasing .github/skills/bio-long-read-sequencing-haplotype-phasing && 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-long-read-sequencing-haplotype-phasing" agent skill from https://github.com/GPTomics/bioSkills/tree/main/long-read-sequencing/haplotype-phasing into .github/skills/bio-long-read-sequencing-haplotype-phasing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bio-long-read-sequencing-haplotype-phasing", 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-long-read-sequencing-haplotype-phasing -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-long-read-sequencing-haplotype-phasing --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/long-read-sequencing/haplotype-phasing .opencode/skills/bio-long-read-sequencing-haplotype-phasing && 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-long-read-sequencing-haplotype-phasing" agent skill from https://github.com/GPTomics/bioSkills/tree/main/long-read-sequencing/haplotype-phasing into .opencode/skills/bio-long-read-sequencing-haplotype-phasing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bio-long-read-sequencing-haplotype-phasing", 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-long-read-sequencing-haplotype-phasingPhases small variants, SVs, and methylation from Oxford Nanopore and PacBio long reads (read-backed/physical phasing) with WhatsHap, LongPhase, or HiPhase, and haplotags the BAM (HP/PS tags) for…
Bio Long Read Sequencing Haplotype Phasing is an agent skill from GPTomics/bioSkills. Phases small variants, SVs, and methylation from Oxford Nanopore and PacBio long reads (read-backed/physical phasing) with WhatsHap, LongPhase, or HiPhase, and haplotags the BAM (HP/PS tags) for allele-resolved downstream analysis. Covers why phase blocks break at het-sparse gaps (read length x heterozygosity), why phasing the VCF is useless until the BAM is haplotagged, the GT-pipe/PS and read HP/PS tag spec, reporting block N50 with switch error, the diploid-assumption/CNV/haploid-region traps, trio phasing as…
Its SKILL.md is about 3.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files (for example `examples/longphase_sv_cophasing.sh`, `examples/phase_and_haplotag.sh` and `usage-guide.md`).
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), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
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 Long Read Sequencing Haplotype Phasing loads about 3.1k tokens when it runs. Until then it costs about 207 tokens; SKILL.md has 1,341 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). 1,341 words, ~3,110 tokens.
.claude/skills/bio-long-read-sequencing-haplotype-phasing/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.Reference examples tested with: whatshap 2.3+, longphase 1.7+, samtools 1.19+, tabix/htslib 1.19+.
Before using code patterns, verify installed versions match. If versions differ:
<tool> --version then <tool> --help to confirm flagsBehavior to record:
whatshap phase --reference enables realignment mode (rescues indel phasing on error-prone long reads); omitting it falls back to lower-quality genotype-only phasing.--max-coverage 15 (WhatsHap) is a runtime downsampling cap, not a minimum-depth requirement.If code throws an error, introspect the installed tool (whatshap phase --help, longphase --help) and adapt the example to the actual API rather than retrying.
"Phase my long-read variants" -> Reconstruct haplotypes directly from reads that span heterozygous sites, then haplotag the BAM so downstream tools can see the phase.
whatshap phase -o phased.vcf.gz --reference ref.fa --indels variants.vcf.gz aln.bam then whatshap haplotag -o haplotagged.bam --reference ref.fa phased.vcf.gz aln.bamThis is read-backed (physical, panel-free) phasing of a single sample. Statistical/reference-panel phasing for imputation lives in phasing-imputation/haplotype-phasing; building phased haplotype contigs lives in genome-assembly/hifi-assembly.
Read-backed phasing is sample-intrinsic and panel-free (the haplotypes are exactly what this individual's reads physically witness), with two load-bearing consequences:
phase writes the VCF; haplotag writes the BAM - they are different products. whatshap phase / longphase phase set GT pipe (0|1) and a PS phase-set in the VCF; they do NOT touch the BAM. Every read-level downstream tool (modkit --partition-tag HP for allele-specific methylation, pb-CpG-tools --hap-tag HP, Severus for phased SVs, IGV color-by-HP, whatshap split) keys on the per-read HP tag that ONLY haplotag writes. A user who runs phase and stops has a phased VCF and an un-haplotagged BAM, and the downstream step silently produces only an ungrouped partition. Triage: samtools view haplotagged.bam | grep -m1 'HP:i:'.Switch-error accuracy is comparable across read-based tools (~0.1-0.4% on long reads); choose on speed, SV/mod co-phasing, platform, and pedigree.
| Scenario | Tool | Why |
|---|---|---|
| Careful default; indel phasing | WhatsHap (--reference --indels) | realignment mode rescues indels; widest downstream familiarity |
| Parents/pedigree sequenced | WhatsHap --ped (PedMEC) | the gold standard - chromosome-scale, lowest switch error |
| Whole-genome ONT speed | LongPhase (--ont) | ~10x faster; 30x human in ~1 min |
| Co-phase SVs / methylation into long blocks | LongPhase (--sv-file/--mod-file) | a phased SV bridges het-sparse gaps; block N50 ~25 Mbp |
| PacBio HiFi, joint small+SV+STR | HiPhase | PacBio-native one-pass phasing |
| Multi-tech (Hi-C / 10x) | HapCUT2 | models Hi-C/linked-read error |
| Inside PEPPER-Margin-DeepVariant | margin | legacy embedded haplotagger |
Clair3 uses WhatsHap (or LongPhase) internally to phase its het SNPs and haplotag the BAM feeding its full-alignment model - this skill owns that phase->haplotag mechanism (see clair3-variants).
| Layer | Tag | Meaning |
|---|---|---|
| VCF (per variant) | GT with ` | vs/` |
| VCF (per variant) | FORMAT/PS (Integer) | phase-set / block id; variants sharing a PS are phased relative to each other (conventionally the first variant's position) |
| BAM (per read) | HP:i:1 / HP:i:2 | the haplotype this read was assigned to (written by haplotag) |
| BAM (per read) | PS:i:<int> | the phase set the read's assignment belongs to (matches the VCF PS) |
Unassigned reads carry NO HP tag (not HP:i:0). Do not confuse the VCF HP FORMAT tag (GATK style) with the BAM HP read tag.
| Metric | Tool | Trap |
|---|---|---|
| phase-block N50/NG50 | whatshap stats | contiguity, not correctness; gameable by over-joining blocks (which raises switch errors) |
| phased fraction | whatshap stats | a tool can phase fewer easy sites to look better |
| switch error rate | whatshap compare | the primary accuracy number |
| switch vs flip decomposition | whatshap compare | a long switch propagates (damaging); a flip/short switch self-corrects (one wrong variant) - quote the decomposition |
| Hamming distance | whatshap compare | hypersensitive to switch position (a switch near a block start flips half the block) |
Long blocks with a high switch rate are worse, not better, than honest short blocks. Benchmark against a trio-/strand-seq-phased GIAB truth.
# WhatsHap: phase (VCF), then haplotag (BAM). --reference enables realignment for indels.
whatshap phase -o phased.vcf.gz --reference ref.fa --indels variants.vcf.gz aln.bam
tabix -p vcf phased.vcf.gz
whatshap haplotag -o haplotagged.bam --reference ref.fa \
--output-haplotag-list htlist.tsv.gz phased.vcf.gz aln.bam
samtools index haplotagged.bam
# Quality
whatshap stats --gtf blocks.gtf phased.vcf.gz # block N50, count, fraction
whatshap compare --names truth,mine truth.vcf.gz phased.vcf.gz # switch error, flip decomposition
# Trio (gold standard) - --ped takes a PED file, not mother/father/child args
whatshap phase -o trio.vcf.gz --reference ref.fa --ped family.ped joint.vcf.gz mother.bam father.bam child.bam
# LongPhase: faster whole-genome, co-phase SNP+indel+SV(+5mC) into long blocks
longphase phase -s snps.vcf --indels --sv-file svs.vcf -b aln.bam -r ref.fa -o phased -t 16 --ont
longphase haplotag -s phased.vcf --sv-file phased_SV.vcf -b aln.bam -r ref.fa -o haplotagged -t 16
# Downstream consumer example: allele-specific methylation
modkit pileup haplotagged.bam asm/ --ref ref.fa --cpg --combine-strands --partition-tag HPTrigger: running phase and pointing a read-level tool at the original BAM. Mechanism: phase writes the VCF only; the BAM HP tag comes from haplotag. Symptom: modkit returns only an ungrouped partition; IGV shows one color; Severus reports no phased SVs - all with no error. Fix: run haplotag; verify samtools view ... | grep HP:i:.
Trigger: a homozygosity-rich or inbred sample phasing into many short blocks. Mechanism: no intervening hets to link across a long homozygous run - intrinsic, not tool failure. Symptom: low block N50 despite good reads. Fix: expect it; use ultra-long reads or co-phase SVs (LongPhase) to bridge sparse-het gaps; only trio/Hi-C makes it chromosome-scale.
Trigger: whatshap phase without --reference. Mechanism: without realignment, allele support for indels in error-prone reads is noisy. Symptom: low indel phasing / errors. Fix: always pass --reference ref.fa (and --indels) on long reads.
Trigger: phasing chrX/Y/MT in an XY sample, or inside a CNV/segdup. Mechanism: the two-haplotype model is false there (hemizygous, >2 or 1 haplotype, or collapsed paralogs). Symptom: spurious micro-blocks, HP counts far from 50/50. Fix: treat phasing there as unreliable; do not interpret it as biology.
Trigger: comparing phasers on block N50. Mechanism: N50 is inflated by over-joining, which raises switch errors. Symptom: "longer blocks" that are actually worse. Fix: report block N50 AND switch error together; use the flip decomposition.
| Threshold | Source | Rationale |
|---|---|---|
| Total depth ~15-20x for confident phasing | phasing practice | per-haplotype depth is ~half; below ~10x blocks fragment |
--max-coverage 15 is a runtime cap | WhatsHap | wMEC is exponential in per-site coverage; >15x is redundant, not required |
| long-read switch error ~0.1-0.4% | benchmarks vs trio truth | the achievable accuracy band |
| LongPhase SNP+SV block N50 ~25 Mbp | Lin 2022 | co-phasing SVs bridges het-sparse gaps (vs ~10-15 Mbp SNP-only) |
| ASM wants ~20x total | methylation practice | each haplotype must clear the ~10x per-site floor |
| Error / symptom | Cause | Solution |
|---|---|---|
modkit --partition-tag HP has only an ungrouped partition | BAM never haplotagged | run whatshap haplotag / longphase haplotag |
--trio flag not recognized | the flag is --ped | pass a PED file: --ped family.ped |
| Poor indel phasing | --reference omitted | add --reference ref.fa --indels |
| 0 reads usable in phase | BAM @RG sample != VCF sample | --ignore-read-groups (or fix sample names) |
longphase --platform ont errors | platform is a bare flag | use --ont or --pb |
| Spurious phasing on chrX/CNV | diploid assumption violated | treat as unreliable; exclude haploid/CNV regions |
-Y so supplementaries are taggable)modkit --partition-tag HP© 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 3 other files in long-read-sequencing/haplotype-phasing 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 Long Read Sequencing Haplotype Phasing 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 Long Read Sequencing Haplotype Phasing this skillGPTomics/bioSkills | 1.2k | 1 repos | ~3.1k | 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
Phases small variants, SVs, and methylation from Oxford Nanopore and PacBio long reads (read-backed/physical phasing) with WhatsHap, LongPhase, or HiPhase, and haplotags the BAM (HP/PS tags) for…. Bio Long Read Sequencing Haplotype Phasing is an agent skill from GPTomics/bioSkills. Phases small variants, SVs, and methylation from Oxford Nanopore and PacBio long reads (read-backed/physical phasing) with WhatsHap, LongPhase, or HiPhase, and haplotags the BAM (HP/PS tags) for allele-resolved downstream analysis.
Bio Long Read Sequencing Haplotype Phasing fits situations like: phasing long-read variants; haplotagging reads for allele-specific methylation/expression; choosing WhatsHap vs LongPhase vs HiPhase; assessing phasing quality.
Run `npx skills add GPTomics/bioSkills --skill bio-long-read-sequencing-haplotype-phasing -a claude-code`. Or copy the skill folder (long-read-sequencing/haplotype-phasing in GPTomics/bioSkills) into .claude/skills/bio-long-read-sequencing-haplotype-phasing in your project. Claude Code loads it when a task matches its description.
Run `npx skills add GPTomics/bioSkills --skill bio-long-read-sequencing-haplotype-phasing -a codex`. Or copy the skill folder (long-read-sequencing/haplotype-phasing in GPTomics/bioSkills) into .agents/skills/bio-long-read-sequencing-haplotype-phasing 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-long-read-sequencing-haplotype-phasing -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-long-read-sequencing-haplotype-phasing, .gemini/skills/bio-long-read-sequencing-haplotype-phasing, .github/skills/bio-long-read-sequencing-haplotype-phasing and .opencode/skills/bio-long-read-sequencing-haplotype-phasing in your project.
Going by SKILL.md and its folder, Bio Long Read Sequencing Haplotype Phasing needs a shell for the scripts in its folder. Our summary lists: A Bash shell.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. 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 Long Read Sequencing Haplotype Phasing is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.1k tokens (SKILL.md is roughly 12k 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 Long Read Sequencing Haplotype Phasing: 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.