Why it matters
Reads are inputs to later processing, not finished conclusions. Their quality, sample association, and handling affect the reliability of alignments and variant calls. Retaining reads can also preserve information absent from a summary report.
A practical example
In a hypothetical workflow, an instrument produces many reads, software aligns them, and another stage identifies candidate variants. Each stage changes the representation while relying on the earlier sample identity.
An important distinction
A read can contain measurement errors, and an unusual read does not by itself prove contamination or tampering. Interpretation depends on the collection of reads, quality measures, and the validated behavior of the workflow.
Sources and further reading
- PRIMARY SOURCE SAM/BAM, CRAM, and VCF format specifications
The example above is hypothetical. Related cases provide context; they do not imply that every case involved this mechanism.