What is bio-comparative-genomics-synteny-analysis?

A guide to comparing the order and structure of genes across genomes. Synteny means that genes remain in corresponding blocks, while structural rearrangements are changes such as inversions, insertions, or moved regions.

Use it to find conserved gene blocks, detect rearrangements and structural variation, and create visual comparisons between related or distant species.

It helps reveal how genomes have changed during evolution and avoids errors caused by strict input formats required by some comparison tools.

bio-comparative-genomics-synteny-analysis — Skill for Claude Code and

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 synteny-analysis

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/synteny-analysis/github.svg)](https://agentmods.dev/skills/gptomics/bioskills/synteny-analysis)

Your own site

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

Per session 192 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 8,918 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. 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	$0.00192	$0.08918
Opus 5	$0.00096	$0.04459
Sonnet 5	$0.00038	$0.01784
Haiku 4.5	$0.00019	$0.00892

Measured 7d ago against content hash b1450aa239b0, 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-synteny-analysis scanned grade A with 0 findings 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/synteny_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.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

bio-comparative-genomics-synteny-analysis — 97% identical, 36 lines differ

comparative-genomics/synteny-analysis/SKILL.md · 478 lines

How it starts

The opening of the file, as written. The whole thing — 478 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Version Compatibility

Reference examples tested with: MCScanX 1.0+ (wyp1125/MCScanX commit 2020+), JCVI 1.4.21+ (Python port of MCScan), GENESPACE 1.4.0+ (Lovell 2022 eLife 11:e78526), SyRI 1.7.1+ (Goel 2019 Genome Biol 20:277), plotsr 1.1.1+, AnchorWave 1.2.5+ (Song 2022 PNAS 119:e2113075119), i-ADHoRe 3.0.01+, SynNet (Zhao 2017 Plant Cell 29:1278), ntSynt 1.0.4+ (2024), minimap2 2.28+, MUMmer 4.0.0+, OrthoFinder 3.0+, R 4.4+. plotsr requires pysam 0.22+ and seaborn 0.13+.

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

CLI: MCScanX -h; syri --version; python -m jcvi.compara.catalog ortholog --help
R: packageVersion('GENESPACE'); ?run_genespace
Python: pip show jcvi

If code throws MCScanX: argument bad format, syri: input alignment file missing required columns, or GENESPACE: GFF parse error, these tools have brittle input parsing: MCScanX requires 4-column species_chr gene start end BED (non-standard), JCVI expects 4-column simple BED, GENESPACE requires GFF3 with gene feature type. Pre-process with jcvi.formats.gff bed or custom AWK.

Synteny Analysis

"Compare genome architecture between these species" -> Detect conserved gene order (synteny) and infer rearrangement history. Synteny is NOT the same as collinearity: synteny is "genes on same chromosome", collinearity is "same order on same chromosome" (modern usage often conflates them). The choice of tool depends on whether the question is gene-level co-linearity (MCScanX, JCVI), whole-genome structural rearrangements (SyRI, AnchorWave), multi-genome macrosynteny (GENESPACE, ntSynt), or synteny-aware orthology (GENESPACE, ProteinOrtho-synteny). Repeat-masking quality is the dominant determinant of result reliability -- unmasked TEs produce ~100x more false anchor pairs than real syntenic anchors.

CLI: MCScanX for collinear gene blocks via dynamic programming
CLI: python -m jcvi.compara.catalog ortholog A B for JCVI/MCScan Python pipeline
R: run_genespace() (Lovell 2022) for orthology-anchored riparian plots + pan-gene tracks
CLI: syri for inversion / translocation / duplication detection
CLI: anchorwave proali for sequence-level WGD-aware synteny

Read the full file on GitHub · 478 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 · 478 lines · 192 tokens per session scan A b1450aa239b0

Subscribe to this mod's changes

bio-comparative-genomics-synteny-analysis is a skill published in the GitHub repository GPTomics/bioSkills (1,199 stars, last pushed 26d ago), licensed MIT. It adds 192 tokens to every session and 8,918 once invoked, about $0.0010 per session on Opus 5. A static security scan graded it A with 0 findings. 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