Choosing depth for the question rather than for completeness: why low pass whole genome sequencing gives copy number and ancestry at a fraction of the cost and cannot call individual variants, what a whole genome sequencing kit and the library chemistry inside it decide about coverage evenness and duplicates, where ctdna analysis needs both depth and molecular identifiers because the signal is a small fraction of the total, how a qrt pcr machine still answers a targeted question faster than any sequencing, and what has to be agreed about analysis and storage before a genome scale project starts

Scoping a genome project

1. Match depth to the smallest thing you must detect. Copy number and ancestry survive shallow coverage. Germline variant calling needs moderate depth. Rare somatic variants in a mixture need deep coverage plus molecular identifiers to separate signal from error.
2. Judge library chemistry on evenness. Coverage uniformity and duplicate rate matter more than nominal yield, because uneven coverage leaves regions uncalled at any average depth.
3. Use molecular identifiers where the fraction is small. Tagging original molecules distinguishes a true low frequency variant from an amplification or sequencing error. Without them, low frequency calling is guesswork.
4. Keep a targeted method for targeted questions. When the variant is known and the question is present or absent, amplification is faster and cheaper than sequencing. Not everything needs a genome.
5. Plan storage and analysis before generating data. Genome scale data is large and long lived. Where it lives, who pays after the project and how it is analysed reproducibly are decided at the start or not at all.
6. Agree deliverables including the pipeline. Raw reads, alignments, variant calls with their filters, the reference and annotation versions, and runnable code. A variant table alone cannot be re-analysed.

Average depth hides the problem

A stated average coverage says nothing about the regions that received almost none, and those regions are systematically the same ones between samples. Uniformity, not average, is what determines callability.

Ask for per region coverage from validation samples, and check the regions your question depends on.

Data outlives the project

Genome scale data is generated in weeks and stored for years, and the storage cost accrues to whoever inherits it. Deciding where it lives and who pays is part of the project plan.

Keep the raw reads and the pipeline; intermediate files can usually be regenerated and are the bulk of the volume.

Common questions

What can shallow coverage answer?

Copy number, large structural features and ancestry, at a small fraction of the cost. It cannot reliably call individual variants, and describing it as whole genome sequencing without the depth caveat overstates it.

Why do rare variants need molecular identifiers?

Because at low allele fraction the true signal is comparable to the error rate. Tagging original molecules lets errors introduced after tagging be identified and removed.

Is sequencing always better than amplification?

No. For a known variant with a yes or no answer, a targeted amplification assay is faster, cheaper and easier to validate. Sequencing earns its place when the question is open.

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