# HomeGenomics

> A practical handbook that helps developers read and understand their own and their family's genomic and transcriptomic data.

Your genome is yours. Get comfortable reading and understanding it, one step at a time.

- [Get started](/en/start/intro/)

## What is this site for?

HomeGenomics is a practical handbook that helps **developers read and understand their own and their family's genomic and transcriptomic data**. It looks beyond the summary report from a testing provider to examine how raw data is produced and how evidence supports an interpretation.

Now that AI agents can handle execution, memorizing commands matters less than being able to **understand the underlying principles, specify what to examine, and interpret both the meaning and the limits of a result**. HomeGenomics practices an approach in which the agent handles execution while the reader owns the questions and judgment.

The starting point is a **real case**. GitLab co-founder [Sid Sijbrandij](/en/start/case-sid/) published his rare-cancer data and documented how he worked with specialists to narrow down treatment candidates. We follow that case to learn how to **find a signal in data, check it against other evidence, and distinguish a plausible interpretation from its limits**.

The published learning paths now cover **bulk RNA-seq and single-cell RNA-seq**. They connect concepts from library preparation and FASTQ processing to expression matrices, quality control, interpretation, and comparisons across samples. DNA variant analysis is planned next.

## Learn from real cases

Using Sid's published material and public research datasets, we examine how an analysis question is formed between real data and a possible treatment candidate.

## Let the agent execute

Step-by-step prompts delegate environment setup, CLI commands, and Python execution. The reader defines the inputs, comparison, outputs, and validation checks, then reviews the result.

## Understand it with your family

Relatives share some genetic information. We learn to separate inherited variants from tumor-acquired changes and to confirm family-relevant findings through genetic counseling and validated testing.

## Study the limits too

We examine data quality, comparison choices, and uncertainty, then separate supported conclusions from questions that still require validation.