Documentation / Cohort Analysis / Quality Control
Study Quality Control
Folklore computes per-sample summary metrics from each completed Variant Analysis result and compares selected metrics with the other successfully read samples in the same Study. The purpose is to identify technical or compositional differences that require review before cohort-level interpretation.
Reported Metrics
| Metric | What Is Reported | Used for Outlier Flag |
|---|---|---|
| Variant count | Total classified variant rows for the sample. | Yes |
| Ti/Tv ratio | The ratio of single-nucleotide transitions to transversions. | Yes |
| Het/Hom ratio | The ratio of heterozygous to homozygous-alternate calls. | Yes |
| Mean depth | Mean recorded read depth across variants with a depth value. | No; displayed for review |
Current Outlier Rule
A successfully read sample is marked OUTLIER when its variant count, Ti/Tv ratio, or Het/Hom ratio is more than 2 sample standard deviations from the Study mean. A deviation in any one of the three metrics is sufficient. Mean depth is reported but is not part of the current automated outlier rule.
QC Status Meanings
The sample result was readable and none of the three automated cohort-relative metrics exceeded the current outlier boundary.
The result was readable, but at least one automated metric differed from the Study mean by more than the current boundary. The recorded reason identifies the metric or metrics.
The expected classified result was missing or could not be read. This is a processing or data-availability failure, not a statistical outlier.
How to Review an Outlier
Confirm the sample identity, sequencing type, reference build, and expected capture design.
Compare raw coverage and calling QC with the laboratory source data, especially when mean depth or variant count differs.
Check whether ancestry, consanguinity, sex-chromosome content, or a genuine biological feature could explain the difference.
Review whether the Study combines different laboratories, callers, panels, or processing versions.
Resolve failed or unintended samples and rerun the Study before relying on cohort-level results.
Interpretation Limits
These are cohort-relative checks. PASS does not prove that a sample is uncontaminated, correctly labeled, or technically equivalent to every other sample. OUTLIER does not prove an error. In a small or heterogeneous Study, the mean and standard deviation can be unstable or reflect the cohort composition itself.
Principal-component batch or ancestry detection is not part of the current production QC result. The present QC should therefore be combined with laboratory-level QC, provenance review, and an appropriate Study design.
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