Tutorials
Working with your .genome
Understanding your .genome bundle
Learn what your .genome bundle is, how it differs from raw sequencing files, and how to use it as the starting point for AI-assisted genome exploration.
You will be able to open a .genome bundle, understand what each file is for, and choose the right starting point for a question.
Your first conversation with your genome
Start with a grounded first session: inspect the bundle, ask one narrow question, follow evidence, and save the workflow for later.
You will have a reusable first-session prompt and a method for turning one answer into a deeper investigation.
Open your .genome in Codex
Set up a clean Codex workspace and prevent the model from guessing what is inside your genome files.
You will have a reliable Codex workflow for file-based genome exploration.
Use Codex with your .genome
Use a local coding agent to inspect your .genome files, search annotations, write reports, and build repeatable exploration workflows.
You will know how to use Codex or Claude Code to work with your .genome locally while preserving file references and evidence.
Read AI answers critically
Learn how to audit genome answers by separating direct evidence, annotation context, research context, inference, and overreach.
You will have a practical review checklist for any answer generated from your .genome.
Write better genome prompts
Turn broad genome questions into precise prompts that ask for files, genes, variants, evidence, sources, and follow-up questions.
You will be able to write prompts that produce specific, inspectable .genome answers instead of generic genetics essays.
Get citations from AI answers
Teach AI tools to attach provenance to genome claims so you can see which claims came from your .genome and which came from research context.
You will have a citation and provenance prompt you can run after any .genome answer.
Build reusable prompt templates
Turn one good .genome exploration into a reusable template for future genes, variants, traits, papers, and Genome Intelligence cards.
You will have a small prompt library that can be reused across topics while preserving evidence and source requirements.
FASTQ vs gVCF vs .genome
Understand raw reads, variant calls, confident reference regions, and why .genome is the AI-ready layer built for exploration.
You will know what each file type preserves, when to use it, and how .genome fits on top of sequencing data.
What 30x actually means
Understand sequencing coverage, why 30x is a common whole-genome standard, and how coverage supports confidence without becoming certainty.
You will know how to ask about coverage and quality context inside your .genome without overinterpreting it.
Use Genome Intelligence in your workflow
Learn how to move from a live research card into a deeper, file-grounded conversation with your own .genome.
You will know how to copy a Genome Intelligence prompt, adapt it to your data, and follow the evidence in your own file.
Build with .genome
Use .genome as a structured context layer for genome-aware products, agents, local tools, and developer workflows.
You will understand the main build paths: read files locally, expose tools through MCP, or integrate with the Genome API.