Use when analyzing FASTQC quality reports from sequencing data, identifying quality issues in NGS datasets, or troubleshooting sequencing problems. Interprets quality metrics and provides actionable recommendations for RNA-seq, DNA-seq, and ChIP-seq data.
Install with Tessl CLI
npx tessl i github:aipoch/medical-research-skills --skill fastqc-report-interpreter85
Does it follow best practices?
If you maintain this skill, you can automatically optimize it using the tessl CLI to improve its score:
npx tessl skill review --optimize ./path/to/skillValidation for skill structure
Application-specific quality thresholds and issue diagnosis
Per-base quality threshold
100%
100%
Per-sequence quality threshold
100%
100%
N content threshold
100%
100%
Adapter content threshold
66%
100%
Duplication RNA-seq context
66%
100%
Duplication general threshold
100%
100%
Read-end trimming recommendation
40%
100%
Trim tool recommendation
100%
100%
Sequence bias cause diagnosis
100%
100%
Primer randomization recommendation
25%
50%
PASS/WARNING/FAIL status used
100%
62%
Proceed recommendation
70%
100%
Without context: $0.2919 · 2m 9s · 12 turns · 19 in / 6,212 out tokens
With context: $0.6734 · 2m 51s · 26 turns · 214 in / 9,702 out tokens
Batch analysis and programmatic API usage
Uses FASTQCInterpreter class
100%
100%
Uses interpret_report method
80%
100%
Produces CSV output
100%
100%
Sample1 classified as good
100%
100%
Sample3 classified as fail
100%
100%
Per-base quality thresholds applied
80%
100%
Adapter content thresholds applied
80%
100%
Duplication thresholds applied
87%
100%
CSV has per-metric columns
100%
100%
Workflow documented
100%
100%
PASS/WARNING/FAIL terminology
90%
100%
Without context: $0.6854 · 2m 33s · 42 turns · 223 in / 9,562 out tokens
With context: $0.5710 · 1m 57s · 30 turns · 2,208 in / 6,485 out tokens
CLI usage and ChIP-seq specific interpretation
CLI --application flag
100%
70%
CLI --input flag used
100%
62%
Adapter content classified as FAIL
100%
100%
Adapter tool recommendation
100%
100%
Adapter cause identified
50%
100%
Sequence bias cause identified
100%
100%
Sequence bias recommendation
37%
100%
ChIP-seq duplication context
100%
100%
Per-base quality passes
100%
100%
Issues JSON has cause fields
100%
100%
FAIL requires action
100%
100%
Without context: $1.1107 · 4m 8s · 46 turns · 261 in / 12,918 out tokens
With context: $0.8467 · 3m 27s · 35 turns · 326 in / 11,732 out tokens
Table of Contents
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