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Bioconductor Organismdbi

Organization
bioMate-AI
bioconductor-organismdbi

The package enables a simple unified interface to several annotation packages each of which has its own schema by taking advantage of the fact that each of these packages implements a select methods.

Overview

PublisherbioMate-AI
Repositorybiomate-bioconductor-kb
Skill namebioconductor-organismdbi
Stars
804
Forks
66
Bundled files
Instructions only
Links
Skill sourceRepository
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by bioMate-AI on GitHub. Read the source before you install it.

Installation

Install the Bioconductor Organismdbi AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/bioMate-AI/biomate-bioconductor-kb/tree/main/skills/genomics/organismdbi
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/bioMate-AI/biomate-bioconductor-kb.git /tmp/biomate-bioconductor-kb
mkdir -p .claude/skills
cp -r /tmp/biomate-bioconductor-kb/skills/genomics/organismdbi .claude/skills/bioconductor-organismdbi
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Bioconductor Organismdbi in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Bioconductor Organismdbi on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Bioconductor Organismdbi is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

OrganismDbi

Dependencies & Environment

Package-intrinsic requirements from the Bioconductor landing page — reproduce in any R environment.

  • Version: 1.54.0 · Bioconductor: 3.23 · R: ≥ 4.6
  • Depends: BiocGenerics, AnnotationDbi, Seqinfo, GenomicFeatures
  • Imports: DBI, BiocManager, Biobase, graph, RBGL, S4Vectors, IRanges, GenomicRanges
  • System requirements: URL
  • Install: BiocManager::install("OrganismDbi")

When to Use

  • Unified Annotation Queries: Querying multiple annotation resources (e.g., TxDb and OrgDb) simultaneously through a single unified interface using select.
  • Custom Meta-Package Building: Building custom OrganismDbi meta-packages (like Homo.sapiens) that link genome-centric and gene-centric databases using makeOrganismPackage.
  • Feature Extraction: Extracting genomic features (transcripts, exons, cds) mapped directly to gene symbols or other identifiers using transcripts, exons, or cds.
  • Grouped Feature Extraction: Grouping genomic features by a specific identifier (e.g., by gene) using transcriptsBy, exonsBy, or cdsBy.

When NOT to Use

  • Non-Model Organisms: When working with non-model organisms that do not have pre-built OrgDb or TxDb packages available to link together.
  • Cyclic Graph Relationships: When the relationships between your annotation packages present more than one pathway between any two nodes/objects (the package cannot handle cycles in the graph).

Data Requirements

  • Annotation Packages: Installed Bioconductor annotation packages (e.g., org.Hs.eg.db, TxDb.Hsapiens.UCSC.hg19.knownGene, GO.db).
  • Graph Data: A list of short two-element character vectors representing foreign key relationships (e.g., graphData) when building custom packages.

Key Parameters

  • keys: The character vector of keys to search for in select or keys.
  • keytype: The type of input keys (e.g., "ENTREZID") provided to select or keys.
  • columns: The columns of information to retrieve (e.g., c("TXNAME", "SYMBOL")) in select, transcripts, or transcriptsBy.
  • by: The grouping factor (e.g., "gene") used in transcriptsBy.
  • pkgname: The name of the custom package to create (e.g., "Homo.sapiens") in makeOrganismPackage.
  • graphData: The list expressing how different packages relate to each other via foreign keys in makeOrganismPackage.

Best Practices

  • Inspect Fields: Use keytypes() and columns() to inspect valid query fields before executing a search.
  • Use Select: Prefer using the unified select() method to retrieve multi-database annotations in a single tabular format.
  • GRanges Integration: When extracting genomic ranges, use functions like transcripts(Homo.sapiens, columns=...) to get GRanges objects pre-annotated with gene metadata.
  • Consistent Builds: Take extra care to ensure that the different packages used in makeOrganismPackage are from the same build (e.g., hg19).

Common Pitfalls

  • Conflicting Package Schemas: Mixing incompatible TxDb and OrgDb versions. Fix: Ensure the underlying TxDb and OrgDb packages correspond to the same genome assembly and annotation release.
  • Non-Unique Columns: Having more than one example of each field across supporting packages. Fix: Ensure all values returned by columns are unique across ALL of the supporting packages before using makeOrganismPackage.
  • Graph Cycles: Providing a graphData list with multiple pathways between nodes. Fix: Choose exactly one foreign key relationship to connect any two packages in your graph.

Alternatives

  • AnnotationDbi: The base package for querying individual OrgDb databases.
  • GenomicFeatures: Specifically for managing and querying TxDb transcript databases.

Citations

  • Carlson M, Atiku Mustapha A (2026). OrganismDbi: A meta framework for Annotation Packages.

References

Run this on BioMate

This skill is the knowledge layer — when, why, and how to use organismdbi. To run this analysis on your own data with managed compute, automated QC, and reproducible outputs, use BioMate — free to start.

▶ Open organismdbi on BioMate →

Frequently asked questions

What does the Bioconductor Organismdbi AI skill do?

The package enables a simple unified interface to several annotation packages each of which has its own schema by taking advantage of the fact that each of these packages implements a select methods.

Why use Bioconductor Organismdbi on TypingMind?

Because you install it once and use it with any model. Bioconductor Organismdbi is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Bioconductor Organismdbi in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/bioMate-AI/biomate-bioconductor-kb/tree/main/skills/genomics/organismdbi. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Bioconductor Organismdbi?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Bioconductor Organismdbi?

As many as you like. As long as a model supports skills, you can use Bioconductor Organismdbi with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Bioconductor Organismdbi AI skill free?

It is published on GitHub by bioMate-AI. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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