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Apply cohort QC threshold reasoning to per-sample variant metrics.
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Basé sur la classification professionnelle SOC
Compare scientific variables with units, ranges, and quality caveats.
Inspect dataset structure before analysis or visualization.
Evaluate data quality from observed structure and summary evidence.
Choose visual checks that match the inspected data.
Route dataset questions to structure, analysis, or visualization experts.
Choose a plot that confirms numeric conversion integrity.
| name | cohort_qc_thresholds |
| title | Cohort QC Thresholds |
| description | Apply cohort QC threshold reasoning to per-sample variant metrics. |
Use this skill when interpreting per-sample cohort QC metrics. Consider call rate, missingness, heterozygosity, sex-chromosome evidence, and outlier status.
Treat thresholds as decision support, not absolute truth. Explain which metrics triggered a flag and what follow-up would confirm it.
