Oxford Nanopore read end reason QC analysis. Use when analyzing nanopore sequencing quality, checking for adaptive sampling efficiency, investigating read termination patterns, diagnosing sequencing issues, or running QC on POD5/Fast5 data. Integrates with ont-experiments for provenance tracking via Pattern B orchestration. Supports signal_positive, unblock_mux_change, data_service_unblock_mux_change analysis with quality thresholds.
Analyze Oxford Nanopore read end reasons for quality assessment and adaptive sampling efficiency.
Run through ont-experiments for provenance tracking:
ont_experiments.py run end_reasons exp-abc123 --json results.json --plot qc.png
Or standalone:
python3 end_reason.py /path/to/data --json results.json
| End Reason | Description | Expected % |
|---|---|---|
signal_positive | Normal completion | 80-95% |
unblock_mux_change | Adaptive sampling rejection | 0-15% |
data_service_unblock_mux_change | Basecall-triggered rejection | 0-10% |
mux_change | Pore mux change | 1-5% |
signal_negative | Signal lost | <5% |
| Status | Criteria |
|---|---|
| ✓ OK | signal_positive ≥75% |
| ⚠ CHECK | signal_positive <75% or anomalies |
| ✗ FAIL | signal_positive <50% |
| Option | Description |
|---|---|
--json FILE | Output JSON summary |
--csv FILE | Output per-read CSV |
--plot FILE | Output bar chart (PNG/PDF) |
--format FORMAT | Force format (pod5, fast5, summary) |
--quick | Sample 10k reads only |
{
"total_reads": 15000000,
"quality_status": "OK",
"signal_positive_pct": 90.0,
"unblock_mux_pct": 8.0,
"data_service_pct": 1.0,
"end_reasons": {
"signal_positive": {"count": 13500000, "pct": 90.0},
"unblock_mux_change": {"count": 1200000, "pct": 8.0}
}
}