FQC

FQC performs quality control on FASTQ files by running FastQC and aggregating QC metrics to assess the quality of high-throughput sequencing data.

Key Features:

• FastQC execution: Runs FastQC to generate per-sample quality metrics for FASTQ files.
• Result parsing and aggregation: Parses FastQC output and aggregates QC metrics across samples and sequencing runs.
• CSV integration: Incorporates CSV data into aggregated QC outputs to enable inclusion of sample metadata or additional metrics.
• Configurable output: Supports human-readable configuration files for customization of output structure.
• Implementation: Implemented using Python 3 and JavaScript.

Scientific Applications:

• Sequencing quality control: Quality assessment of FASTQ files generated by high-throughput sequencing.
• Per-run summaries: Summarizing and comparing QC metrics across individual sequencing runs.
• Metadata-integrated analysis: Combining QC metrics with CSV metadata for analyses tailored to experimental designs.

Methodology:

Runs FastQC on FASTQ files, parses FastQC results, aggregates QC metrics, and integrates CSV data; implemented in Python 3 and JavaScript and configurable via human-readable configuration files.