Personal science. On your terms.
You are
a study
of one.
Your habits change. Your body responds.
Look closer at what your data can tell you.
Source repository · access required
FIG. 001 / THE INDIVIDUAL
Conceptual DNA visualization
OBSERVATION, NOT PREDICTION
One person. One question.
Did that change
change anything?
A different bedtime. A new evening routine. A question about your own body.
askmygenome compares a baseline window with an intervention window in your Apple Health data. Choose one outcome and inspect the difference, the uncertainty, and what might explain it.
The current prototype studies wearable data. The DNA above is a visual metaphor, not a genome analysis.
A small experiment.
A clear record.
Start with the data you already have.
Keep the question specific.
- 01
Bring your data.
Export Apple Health XML and open it in the local workbench. Your health data stays on your machine.
- 02
Frame the question.
Choose your before and after windows. Mark washout days, exclusions, and confounders that deserve context.
- 03
Read the evidence.
Inspect the effect estimate, missingness, uncertainty, and warnings. Keep the report and its canonical JSON record.
A result is a starting point.
See the signal.
Keep the
uncertainty.
A difference in your data is worth examining. It does not prove what caused it.
The report keeps the estimate beside its limits. Excluded days remain visible. Missing data stays missing.
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Sleep duration
IllustrativeExample difference
between windows
Faded points are excluded from the estimate. The full report includes uncertainty and limitations.
Local by design.
No accounts, persistence, or network calls in the product flow.
Repeatable by code.
Deterministic analysis with parameters, exclusions, versions, and input hash in the record.
Honest about limits.
Retrospective, observational analysis. No causal proof or medical advice.
Get closer
to your data.
A local web page, CLI, and deterministic engine.
One careful question at a time.
Source repository · access required