A working guide to quantifying transcript isoforms from short-read RNA-seq: building a Salmon index, running selective alignment, importing with tximport, testing differential transcript usage with DRIMSeq and DEXSeq, and deciding when the answer requires long reads.
A practical workflow for going from an rsID to a genotype you can trust: resolving coordinates, querying your VCF, falling back to the reads when the VCF is silent, and annotating the result correctly.
Yes, you can measure CRP at home, but only some kits report the low range that matters for cardiovascular risk stratification. How the assay types differ, what the numbers mean, and how to build a usable time series.
Morning, fasted, rested, and identical from draw to draw. Here is which analytes move across the day, what the 48 hours beforehand do to your numbers, and how to write a draw protocol you can repeat for years.
A technical read on epigenetic clocks, blood-chemistry clocks, and survey-based 'bio age' calculators: what each one measures, how precise it is, and how to compute one yourself from your own data.
A working setup for longitudinal biomarker tracking: a schema that survives lab changes, your own analytical and biological variation estimates, reference change values instead of reference ranges, and trend fitting that does not fire on noise.
Two different tests share the name methylation testing: genotyping of one-carbon metabolism genes like MTHFR, and direct measurement of DNA methylation across the genome. This explains what each one measures, how to extract the data yourself, and where the interpretation stops.
A1c and glucose disagree when either your glucose sampling is unrepresentative or your red cell biology and hemoglobin assay distort the glycation measurement. Here is how to separate the two with CGM data, a CBC, an assay method check, and a look at your genome.
A technical walkthrough of DNA methylation testing: array versus bisulfite sequencing versus nanopore, the IDAT-to-beta-value pipeline we would run, which epigenetic clocks are worth computing, and where the measurement stops being informative.
Two very different assays are sold under the name 'methylation panel': a one-carbon biochemistry blood panel and a DNA methylation assay. Here is what each one measures, which files you get, and how to process them yourself.
A technical guide to preventive genetic testing: which variants have actionable evidence, why sequencing depth and file format matter, and how to work with your own VCF without over-reading it.
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 correlating genes, samples, and timepoints in personal RNA-seq data: which transform to use before computing a coefficient, how to filter, how to handle confounders, and how to correlate expression against proteomics, labs, and continuous glucose data.
A concrete walkthrough of bulk RNA-seq: where to get a real example dataset, what the files contain, how to quantify with salmon, and how to get to a gene-level table you can interpret, including the case where you only have your own samples.
A practical pipeline for turning your own bulk RNA-seq FASTQs into quantified gene and transcript expression, with the tool choices, flags, QC thresholds, and failure modes that matter for a single-person longitudinal dataset.
A step-by-step pipeline from raw FASTQ to a filtered, benchmarked VCF for a single human genome, with the tool choices, parameters, and quality checks we would use.
A step-by-step pipeline for taking a 4-5 million variant single-sample VCF and reducing it to a few dozen candidates, with the actual bcftools, ANNOVAR, and slivar commands, plus where the filters lie to you.
A technical assessment of the consumer blood panel companies: who runs the assays, what the $349-$499 membership buys, how to get structured data out, and why a 100-biomarker panel flags something for almost everyone.
Three different things get called a DNA clock. This page covers the one people usually mean, the epigenetic age clock: which assay to run, how to compute the score yourself from IDAT or bedMethyl files, and how much of the number is signal.
A practical walkthrough of going from FASTQ, BAM/CRAM, and VCF files to an actual nucleotide sequence you can read, translate, and check against the reads it came from.