Tag: pharmacogenomics

Which pharmacogenes have real prescribing evidence, what the GeneSight and PRIME Care trials found, and how to call the alleles yourself.

A technical comparison of clinical PGx panels, psychiatry combinatorial reports, and calling star alleles from your own whole-genome data, including the tools, flags, and genes that break.

Pharmacokinetic genotyping of CYP2C19 and CYP2D6 has real clinical guidelines behind it. Panels that claim to predict which antidepressant will work do not. Here is how to get an accurate diplotype call from your own sequencing data.

A working guide to genotype-guided drug response: which genes carry the signal, how to call star alleles yourself, and where arrays fail.

A step-by-step pipeline that turns your own whole-genome data into a normalized and annotated variant set, with the tools and filters we would use.

A technical walkthrough of pharmacogenetic star-allele calling from whole-genome data: which genes have real evidence, why CYP2D6 breaks most pipelines, and how to read a diplotype-to-phenotype report without over-trusting it.

A working guide to interpreting a genetic test result yourself, from verifying the file to knowing which findings need a clinician.

Psychiatric pharmacogenetics is mostly two genes, CYP2C19 and CYP2D6, plus two HLA alleles. Here is what the evidence supports, how to call those genes from whole-genome data with PharmCAT and Cyrius, and where the commercial panels overreach.

A pharmacogenetic test genotypes a small set of drug-metabolism genes and converts them into star-allele diplotypes and metabolizer phenotypes. Here is what that pipeline looks like, which genes are hard to call, and what the result does and does not tell you.

A survey of the labs selling pharmacogenomic testing, what their panels genotype, how strong the clinical evidence is, and how to reproduce (and extend) those calls from your own whole-genome data with PharmCAT, Cyrius, and Aldy.

A direct account of WGS applications, from rare-disease diagnosis to pharmacogenomics, plus the file formats, tools, and flags you need to analyze a 30x genome yourself.

How to go from a whole-genome VCF to CPIC-grade star allele diplotypes for CYP2C19, CYP2D6, DPYD, TPMT and others, which callers to run, and the failure modes that make a clean-looking result wrong.

A plain answer to what genetic screening is, how it differs from diagnostic testing, and how to analyze a whole-genome VCF yourself: gene lists, callers, annotation, coverage failure modes, and when you need a clinician.

Pharmacogenetic testing predicts how fast you metabolize certain antidepressants. How to call the star alleles yourself, and where the calls fail.

A technical account of pharmacogenetic panels, whole-genome sequencing, and the files they produce: coverage requirements, star-allele calling, CYP2D6 copy number, and where prices land in 2026.

Pharmacogenomic testing resolves star alleles in about a dozen drug-metabolism genes and maps them to CPIC phenotypes. Here is what panels cover, why CYP2D6 is the hard part, and how to generate diplotype calls from your own sequencing data.

What pharmacogenomic panels like GeneSight measure, what the trial data show, how to read CYP2D6 and CYP2C19 from your own genome, and what serum drug levels can and cannot tell you.

How to get pharmacogenomic (PGx) results at home, why sequencing beats the saliva-kit panels for most genes, and how to run PharmCAT, Aldy, and HLA typing over your own data without over-reading the output.

A working guide to producing star-allele diplotypes and CPIC phenotypes from your own sequencing data with PharmCAT, Cyrius, and PyPGx, and to reading a commercial PGx report critically.

Whole-genome sequencing processed with PharmCAT and Cyrius gives you more pharmacogenetic information than any branded psychiatric panel, and you keep the data. Here is how to run it and what the evidence supports.

Cash prices for pharmacogenetic panels run from about $50 to over $2,000 for largely the same gene list. Here is what drives the spread, what insurance pays, and how to derive the same star-allele calls from whole-genome data yourself.

A working guide to genetic testing in asymptomatic people. Covers panel versus genome, variant classes short reads miss and when a clinician is needed.

Pharmacogenetic testing reliably predicts how you metabolize a few dozen drugs, and says almost nothing about which antidepressant will work. Here is what the genes cover, how to call the star alleles yourself from whole-genome data, and where the calls break.

A technical comparison of PGx testing companies, what their panels genotype, where they fail on CYP2D6 and DPYD, and how to produce CPIC-grade diplotype calls yourself from whole-genome sequencing.

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.

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.

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.

Pharmacogenomic panels marketed for ADHD medication selection rest on thin evidence for stimulants. Here is what the genotypes predict, which variants have real pharmacokinetic support, and how to extract them from your own sequencing data.

A working guide to taking a 23andMe/Ancestry export or a whole-genome FASTQ, converting it to an annotated VCF, filtering it sensibly, and knowing which results are real.

A technical account of whole genome sequencing as a data product: coverage and chemistry, file formats, a pipeline we would run, and the questions a genome can and cannot answer.