Tag: wgs

A genome explorer is a coordinate browser plus a query layer over your own alignments and variant calls. Here is the stack we would use on a personal 30x whole genome, with the commands, file formats, and failure modes.

"Genome manager" usually means a vendor's web portal for your sequencing results. Here is what that portal does, what it hides, and how to run your own catalog of VCFs, BAMs, expression matrices, and lab panels with tools you already know.

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.

Most consumer wellness DNA tests report array genotypes and low-evidence trait associations. Here is what a genome can and cannot tell a healthy person, which file formats and tools matter, and where the real signal is.

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.

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 comparison of the companies that will sequence or map your genome, what data each one hands back, and how to judge an offer by coverage, read length, and file deliverables rather than marketing copy.

What whole-genome sequencing results contain, which files matter, how to interpret a variant classification, and where the analysis stops and a clinician starts.

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.

What is in a VCF, how to filter it down to variants worth reading, how to read a single variant end to end, and what a negative result does not rule out.

A genome kit is worth buying only if it ships you 30x PCR-free whole-genome sequencing and the underlying files. Here is the spec sheet, the QC commands to run on delivery, and what drugstore DNA kits measure.

A genome report is a filtered summary built on top of your variant calls. Here is what goes into one, which files matter more than the PDF, and what sequencing costs in 2026.

A working pipeline for calling somatic SNVs and indels with GATK Mutect2, from BAM to filtered, annotated VCF, plus what the results mean at low variant allele fraction and where the method stops working.

A step-by-step guide to annotating your personal WGS VCF with Ensembl VEP: cache setup, plugin stack (AlphaMissense, CADD, SpliceAI, LOFTEE, dbNSFP), consequence picking, and turning millions of annotated rows into something you can query.

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 spec for buying whole-genome sequencing: coverage, library prep, file formats, the QC you should run yourself, and what WGS still misses.

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 genetic testing in asymptomatic people: panel vs genome, the variant classes short-read pipelines silently miss, the annotation stack we'd run on our own VCF, and where a clinician is non-optional.

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.

A working guide to variant interpretation software: what each layer of the stack does, which tools we would use for a personal whole genome, and where the interpretation breaks.

The All of Us Research Program stopped returning research DNA results and removed ancestry and trait reports from participant accounts. What you were given, what you never had, and how to get raw genomic data you control.

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 pipeline for taking a personal WGS VCF into R: GDS conversion, quality metrics, ancestry PCA against 1000 Genomes, variant annotation, and polygenic score computation, with the failure modes that silently corrupt each step.

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.

A practical walkthrough for taking a whole-genome VCF, keeping only the variants your caller flagged as PASS, normalizing them, and flattening the result into a table you can query. Includes the failure modes that silently drop real variants.

A practical guide to ordering whole-genome sequencing for yourself: what coverage and read length to insist on, which files to demand, how to check quality yourself, and what the data can and cannot tell you.

A working pipeline for annotating a personal whole-genome VCF: normalize with bcftools, annotate with Ensembl VEP offline, join custom datasets with vcfanno or slivar, then filter down to something you can read.

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.

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 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.

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.

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 worked walkthrough of what real DNA results look like: array text files, VCF lines field by field, coverage and callability checks, annotation with VEP, and what a 'positive' result does and does not mean.

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.

A working guide to reading, normalizing, filtering, annotating, and querying a Variant Call Format file from whole-genome sequencing, including how to get a slice of it into a spreadsheet without breaking it.

Consumer 30x WGS runs $300-600, clinical CLIA-reported WGS runs roughly $1,000-3,000 out of pocket, and the difference is depth, deliverables, and interpretation rather than sequencing chemistry. Here is how to read a price and verify what you received.

A breakdown of consumer, research-core, and clinical whole genome sequencing prices, what each tier gets you in files and coverage, and where the hidden costs sit.

A FoundMyFitness report is a literature annotation layer on top of a consumer genotyping array. Here's how to audit the underlying file, rebuild the analysis yourself, and understand where array data runs out.

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.