15 posts
What a CGM measures, which sensor to buy over the counter, how to get the raw data out as CSV, and the metrics and failure modes that decide whether the two weeks of data mean anything.
What post-meal glucose looks like in people without diabetes, where the 140 and 180 mg/dL thresholds come from, and a protocol for extracting real numbers from your own CGM export.
A practical map of the software that turns raw multi-omics files into results you can query, with the commands, formats, and failure modes that matter for a single person's data.
A working guide to taking personal proteomics data from raw instrument files or NPX tables to a quantitative matrix, QC'd and normalized, and then to within-person statistics you can defend.
A practical guide to wearing a continuous glucose monitor around training: sensor placement, interstitial lag, exporting raw CSV data, the metrics worth computing, and the artifacts that will fool you.
A continuous glucose monitor does not cause fat loss, but it is a good instrument for measuring how you eat. Here is what the data supports, how to run your own meal experiments, and the failure modes that will fool you.
Overnight glucose normally falls to its lowest point of the day a few hours after sleep onset. This page explains what a normal nocturnal curve looks like, how to analyze your own CGM data for real low events, and how to recognize the compression artifacts that mimic them.
A practical guide to wearing a CGM without diabetes: which sensors to buy, how accurate they are, what a normal glucose curve looks like, and how to analyze the raw data yourself.
A practical guide to choosing a continuous glucose monitor as a non-diabetic athlete, getting the raw data out, and analyzing it without over-reading sensor noise.
A working method for turning a raw Libre or Dexcom export into an ambulatory glucose profile, per-meal response curves, and metrics you can defend — including what the numbers can and cannot tell you.
A working guide to pulling your lab data out of patient portals, normalizing it into one machine-readable table, computing derived values yourself, and telling a real change from assay noise.
DNA age tests read cytosine methylation at a few hundred CpG sites and regress it onto chronological age. Here is how the assay works, which clocks are worth running, what the error bars really are, and how to process the raw data yourself.
A practical workflow for taking your RNA-seq FASTQ files to transcript quantification, then using web-based analysis tools for the parts they do well. Includes commands, parameters, cost estimates, and the failure modes that waste the most time.
What the post-meal glucose numbers are for people without diabetes, where the thresholds come from, and how to compute peak, time-to-peak, and incremental AUC from your own CGM export.
A CGM measures the output of your glucose system, not its input. Here is what a sensor can and cannot tell you about insulin sensitivity, and the paired measurements that make the trace interpretable.