19 posts
A step-by-step guide to taking 30x WGS FASTQs from a vendor portal to an annotated, QC-checked variant call set using spot instances, bwa-mem2, DeepVariant, and Nextflow. Includes real costs, memory requirements, and the failure modes that waste a weekend.
A technical guide to getting your DNA sequenced without handing the data to a consumer platform: what each tier of testing can resolve, where the error rates live, and how to store and analyze the files yourself.
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.
What array, exome, and whole-genome testing each measure, which files to insist on, and a concrete pipeline for calling and annotating your own variants.
A practical guide to DNA analysis tools: what works on a 23andMe-style genotype file, what requires FASTQ/BAM/VCF from whole-genome sequencing, and the commands we would run at each step.
A step-by-step guide to going from raw FASTQ files to an aligned CRAM, a benchmarked variant call set, an annotated shortlist, and an RNA-seq expression table, with the actual commands, parameters, and quality thresholds we use.
A practical comparison of DeepVariant, GATK HaplotypeCaller, bcftools mpileup, Strelka2, and Clair3 for calling SNPs from your own whole-genome data, with commands, benchmarks, and the failure modes that matter.
A working stack for analyzing your own whole-genome sequencing data: alignment with BWA-MEM2 or Dragen, variant calling with DeepVariant, annotation with VEP, and interpretation limits you should respect.
A working guide to comparing genomes — your own against the reference and against benchmark truth sets, assembly against assembly, and hundreds of bacterial genomes at once — with the tools, flags, and failure modes that matter.
A step-by-step guide to going from raw FASTQ to a filtered, benchmarked, annotated single-sample VCF, with the tools, flags, and quality numbers we would use ourselves.
Cloning tools like SnapGene and Geneious answer a different question than personal genome analysis. A concrete stack for going from FASTQ to annotated variants, with the tools, flags, file formats, and failure modes that matter.
A working guide to array genotyping versus whole-genome sequencing, the files you get, the tools to run on them, and the failure modes that make confident-looking results wrong.
A working guide to calling, normalizing, annotating, and querying SNPs from your own sequencing or array data, with the specific tools, flags, and failure modes that matter.
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.
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.
How to genotype ABO and RhD from whole-genome sequencing data, which variants matter, where short reads fail, and why a genomic call is not a transfusion-grade answer.
A breakdown of the genomic testing market by category — clinical labs, direct-to-consumer arrays, research-grade sequencing providers, and tumor profiling — with the file formats, coverage depths, and failure modes that decide whether the data is useful to you.