Blog

Whole exome sequencing reads the ~1-2% of your genome that codes for protein. What it finds, what it silently misses, and how to read the files yourself.

A working guide to verifying, converting, and analyzing a personal 30x whole-genome file: checking the reference build, CRAM to BAM, coverage QC, variant calling, haplogroups, and microarray-format exports.

Why array-based consumer kits cap out fast, what a 30x whole genome resolves, which files to demand, and the pipeline we would run on our own data.

Why arrays and consumer health reports fail on rare variants, what to demand from a sequencing provider, and how to run QC and annotation on your own genome.

Why genotyping arrays like 23andMe and AncestryDNA answer a narrow question, what whole-genome sequencing gives you instead, and how to work with the files yourself.

A practical guide to direct-access lab testing: which channels will draw you without a referral, how to design a panel that answers a question, how to control preanalytical variables, and how to get the results out as structured data you can analyze.

DNA.Land stopped accepting uploads and shut down its reports. This guide shows how to take the same raw genotype file, convert it to VCF, impute it, annotate it, and decide which remaining upload sites are worth your data.

Self-pay pharmacogenomic panels run roughly $200-$500, Medicare and commercial plans cover them only under narrow conditions, and a single whole-genome sequence answers the same questions permanently. Here is the pricing, the billing codes, and how to run the interpretation yourself.

A technical comparison of consumer genotyping arrays, clinical panels, and whole-genome sequencing, including the raw file formats each returns and what you can do with them.

A direct look at what a maximal blood panel contains, which assays add real information, where the marketing exceeds the biology, and how to get the raw data in a form you can analyze yourself.

Pharmacogenomic panels like myDNA and GeneSight genotype a short list of variants and return a color-coded report. Here is what those genes do, how to call the same star alleles yourself from whole-genome sequencing, and where the evidence stops.

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 working pipeline for analyzing your own DNA with open source tools, from array raw data to whole-genome FASTQ, including the annotation databases, the commands, and the failure modes that produce wrong answers.

What annual bloodwork is worth drawing, why vendor 'optimal ranges' are weaker than they look, and how to build a personal baseline using biological variation and reference change values.

You can run a nanopore sequencer on your kitchen table and get real reads, but you cannot get clinical-grade whole-genome coverage that way. Here is what home sequencing produces, what it costs, and where sending a sample out is the better call.

A working end-to-end guide to going from FASTQ to a filtered, benchmarked VCF on a personal 30x human genome, with the specific tools, flags, reference files, and failure modes we would use.

What a WGS service delivers, what the files look like, what coverage and platform choices change, and how to tell a real provider from a reseller.

A technical answer to what makes genetic testing private: who holds the raw files, what the consent terms permit, how re-identifiable the data is, and how to store and analyze a genome yourself.

A technical guide to choosing and using a biomarker testing service: what analytes are worth measuring, what the analytical error looks like, how to store and version the results, and where a clinician has to be involved.

The best blood test tracker is a long-format table you control plus fifty lines of Python, not an app. Here is the schema, the LOINC and unit normalization, the reference change value math, and the failure modes that make most trackers wrong.