| name | fastqc-quality-analyzer |
| description | Sequencing quality control skill for assessing read quality, adapter contamination, and sequence composition |
| allowed-tools | ["Read","Write","Glob","Grep","Edit","WebFetch","WebSearch","Bash"] |
| metadata | {"version":"1.0","category":"bioinformatics","tags":["sequence-analysis","quality-control","ngs","qc"]} |
| graph | {"domains":["domain:bioinformatics"],"specializations":["specialization:biomedical-informatics"],"skillAreas":["skill-area:data-analysis","skill-area:python-data-pipelines","skill-area:statistical-analysis"],"workflows":["workflow:experiment-design"],"roles":["role:research-engineer","role:lab-technician"]} |
FastQC Quality Analyzer Skill
Purpose
Enable sequencing quality control for assessing read quality, adapter contamination, and sequence composition metrics.
Capabilities
- Per-base quality score analysis
- Sequence duplication detection
- Adapter content identification
- GC content analysis
- Overrepresented sequence detection
- MultiQC report aggregation
Usage Guidelines
- Run FastQC on all raw sequencing data
- Review quality metrics before alignment
- Identify samples requiring additional QC
- Aggregate results with MultiQC for cohort overview
- Flag samples with quality issues
- Document QC decisions and thresholds
Dependencies
Process Integration
- Whole Genome Sequencing Pipeline (wgs-analysis-pipeline)
- RNA-seq Differential Expression Analysis (rnaseq-differential-expression)
- Long-Read Sequencing Analysis (long-read-analysis)
- Analysis Pipeline Validation (pipeline-validation)