end-reason

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.

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Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/data/end-reason

SKILL.md

End Reason Analysis - ONT QC

Analyze Oxford Nanopore read end reasons for quality assessment and adaptive sampling efficiency.

Integration

Run through ont-experiments for provenance tracking:

bash

ont_experiments.py run end_reasons exp-abc123 --json results.json --plot qc.png

Or standalone:

bash

python3 end_reason.py /path/to/data --json results.json

End Reason Categories

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%

Quality Assessment

Status	Criteria
✓ OK	signal_positive ≥75%
⚠ CHECK	signal_positive <75% or anomalies
✗ FAIL	signal_positive <50%

Options

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

Supported Formats

POD5 (fastest, recommended)
Fast5 (legacy)
sequencing_summary.txt

Output JSON

json

{
  "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}
  }
}