What is bio-comparative-genomics-positive-selection?

A guide to testing whether natural selection has caused certain DNA changes to spread faster than others. It uses codon models that compare changes affecting proteins with changes that do not.

Use it to test genes and evolutionary branches for positive selection, compare selection models, and investigate changes linked to traits or environments.

It helps distinguish evidence of adaptive change from ordinary mutation and evolutionary drift, including selection that affects only particular branches, sites, or time periods.

bio-comparative-genomics-positive-selection

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add GPTomics/bioSkills --skill positive-selection

Clone the repo

git clone --depth 1 https://github.com/GPTomics/bioSkills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/gptomics/bioskills/positive-selection/github.svg)](https://agentmods.dev/skills/gptomics/bioskills/positive-selection)

Your own site

<a href="https://agentmods.dev/skills/gptomics/bioskills/positive-selection"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/positive-selection/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/gptomics/bioskills/positive-selection"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/positive-selection.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 243 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 10,602 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00243	$0.10602
Opus 5	$0.00121	$0.05301
Sonnet 5	$0.00049	$0.02120
Haiku 4.5	$0.00024	$0.01060

Measured 7d ago against content hash 209658b1ef21, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

bio-comparative-genomics-positive-selection scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (examples/selection_analysis.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

# MACSE V2: wget https://bioweb.supagro.inra.fr/macse/releases/macse_v2.07.jar

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

bio-comparative-genomics-positive-selection — 98% identical, 14 lines differ

comparative-genomics/positive-selection/SKILL.md · 495 lines

How it starts

The opening of the file, as written. The whole thing — 495 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Version Compatibility

Reference examples tested with: PAML 4.10.7+, HyPhy 2.5.62+ (BUSTED-MH from Lucaci 2023 MBE 40:msad150; FUBAR-MH from same), datamonkey.org 2024+ for web jobs, IQ-TREE 2.3.6+, MACSE V2.07+, PRANK 170427+, MAFFT 7.526+, PREQUAL 1.02+, HmmCleaner 0.243+, GARD (HyPhy bundled), RDP5 5.59+, ete4 4.1.0+, BioPython 1.84+, scipy 1.13+, polyDFE 2.0+, DFE-alpha 2.16+, GRAPES 1.1.1+, RERconverge 0.3.0+, CSUBST 1.6.0+, PhyloAcc 2.4.0+. Quest-for-Selection benchmark refreshed annually.

Before using code patterns, verify installed versions match. If versions differ:

CLI: codeml (PAML; check by codeml /dev/null -- prints version banner), hyphy --version, gard --help
Python: pip show pyhyphy; introspect ete4 API for tree-labeling
R: packageVersion('RERconverge'); ?correlateWithBinaryPhenotype

If code throws branch-site test LRT non-positive, omega2 hit upper bound 999, MEME ML mixed gradient, the most common cause is alignment error or saturated dS -- inspect alignment with TCS / Guidance2 and dS-vs-divergence-time. PAML 4.10 changed several control-file keywords from 4.9 (getSE = 1 syntax tightened).

Positive Selection Analysis

"Is this gene / branch / site under positive selection?" -> dN/dS (omega = nonsynonymous-to-synonymous substitution rate ratio) framework with explicit choice of WHICH question is being asked (gene-wide / branch-specific / site-specific / episodic) and WHICH null is being rejected. The "test failed because of selection" claim has more known confounders than any other comparative-genomics inference; mandatory pre-screens are: recombination (GARD), alignment errors (PREQUAL or HmmCleaner), saturation (dS distribution), and gBGC (W->S substitution bias). Skipping any one inflates Type-I error to ~20-50% (Anisimova & Yang 2007 MBE 24:1219; Pond 2006 Mol Biol Evol 23:1891).

CLI: codeml PAML site, branch, branch-site models
CLI: hyphy busted hyphy meme hyphy fel hyphy fubar hyphy absrel hyphy relax hyphy gard
Web: datamonkey.org for HyPhy jobs without local install
R: RERconverge::correlateWithBinaryPhenotype() for trait-rate associations
CLI: csubst analyze for convergent substitution
R/CLI: phyloacc for noncoding accelerated evolution

Read the full file on GitHub · 495 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

7d ago First seen · 495 lines · 243 tokens per session scan A 209658b1ef21

Subscribe to this mod's changes

bio-comparative-genomics-positive-selection is a skill published in the GitHub repository GPTomics/bioSkills (1,199 stars, last pushed 26d ago), licensed MIT. It adds 243 tokens to every session and 10,602 once invoked, about $0.0012 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

Scientific

instrument-data-to-allotrope

Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full…

anthropics/knowledge-work-plugins · 123 tokens

matlab

Build, review, migrate, and safely plan MATLAB or GNU Octave numerical workflows, including arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.

K-Dense-AI/scientific-agent-skills · 42 tokens

exploratory-data-analysis

Perform bounded, local exploratory analysis of explicitly supported scientific files. Use for redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain…

K-Dense-AI/scientific-agent-skills · 83 tokens

phylogenetics

Build and analyze phylogenetic trees using MAFFT (multiple alignment), IQ-TREE 2 (maximum likelihood), and FastTree (fast NJ/ML). Visualize with ETE3 or FigTree. For evolutionary analysis, microbial genomics, viral phylodynamics, protein family analysis, and molecular clock studies.

K-Dense-AI/scientific-agent-skills · 68 tokens

research-engineer

An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.

davila7/claude-code-templates · 43 tokens

mapping-to-snomed

Maps clinical concept spans extracted by OpenMed to SNOMED CT concepts through a USER-SUPPLIED terminology server (the user's own Ontoserver, Snowstorm, or UMLS/UTS), never a bundled vocabulary. Use when the user wants to code findings, disorders, procedures, body structures, or substances to SNOMED CT, run an ECL…

maziyarpanahi/openmed · 205 tokens