Why Analyze It Yourself
Why the summary a test company or hospital hands you isn’t enough, and what a developer gains by analyzing the data directly. Sid’s case showed all of this in one person’s body.
1. A summary shows only part
Section titled “1. A summary shows only part”A commercial report or clinical summary shows only a selected few results. But raw data holds hundreds of thousands of variants and the expression of tens of thousands of genes. Working with it directly lets you see what the summary left out: signals like “this gene is unusually overexpressed.” That’s exactly how Sid’s MDM2 treatment began.
2. Data makes the treatment
Section titled “2. Data makes the treatment”Every treatment Sid tried was designed by finding a target to attack in the sequencing data.
Read the data → find the weak point (target) → build a treatment that attacks it
Understanding this flow, and being able to read the data yourself, is what turns you from someone waiting for the options others define into someone helping find them.
3. Data sovereignty
Section titled “3. Data sovereignty”Your genome and transcriptome are the most sensitive personal data there is: and data your family shares. Storing and analyzing the raw data yourself keeps control in your hands, not on a third-party server.
4. It connects to your family, too
Section titled “4. It connects to your family, too”Relatives share much of their genome. A meaningful signal found in one person may apply to parents, children, and siblings too. Being able to analyze it yourself can be a clue to look after risk earlier, at family scale.
5. Prepare while healthy: the biggest lesson
Section titled “5. Prepare while healthy: the biggest lesson”Sid had to generate his data only after he got sick. With no data from his own healthy baseline, he had to borrow an external average (a reference), and that introduced error.
If you secure sequencing data while you’re healthy, then when illness does strike, comparing “healthy me” to “sick me” becomes far more accurate.
Fortunately, sequencing costs have come down enough: bulk RNA-seq for tens of dollars, whole genomes for hundreds. This is no longer the exclusive domain of big labs.
6. Reproducibility
Section titled “6. Reproducibility”Analyzing the way developers already work, scripts, version control, pipelines, means you can reproduce results, re-run them on new data, and verify them. Just as Sid applied the way he built GitLab to his own illness.
Be clear about the limits
Section titled “Be clear about the limits”- Doing it yourself is not a diagnosis. Clinical judgment belongs to professionals.
- Variant and expression interpretation carries real uncertainty. Beware of over-reading.
- Sensitive data brings security and privacy responsibilities.
Next: build up the molecular basics in the first lesson.