fastqc-report-interpreter

What This Skill Does

The fastqc-report-interpreter skill is a powerful diagnostic tool designed for bioinformaticians and researchers working with High-Throughput Sequencing (HTS) data. It acts as an automated quality control assistant, parsing standard FASTQC output files (HTML or text) to interpret complex sequencing metrics. By transforming raw QC data into actionable insights, this skill identifies common sequencing artifacts, library preparation errors, and data quality issues. It supports specialized workflows for RNA-seq, DNA-seq, and ChIP-seq, providing tailored recommendations based on the specific requirements of each experimental design.

Installation

To integrate this skill into your environment, use the OpenClaw CLI tool. Run the following command in your terminal:

clawhub install openclaw/skills/skills/aipoch-ai/fastqc-report-interpreter

Ensure that you have the necessary environment dependencies installed as specified in the source repository documentation before executing the installation command.

Use Cases

• Routine QC Assessment: Automatically screening large batches of FASTQC reports to flag failed sequencing runs before they move into costly downstream alignment or variant calling pipelines.
• Troubleshooting Library Prep: Identifying high duplication levels or adapter contamination patterns that suggest issues with PCR cycle counts, low-input library preparation, or purification steps.
• Optimizing Trimming Parameters: Evaluating sequence quality deterioration at the 3' end of reads to calculate the precise trim length required to retain high-confidence data.
• Cross-Sample Comparison: Analyzing batch uniformity across multiplexed samples to detect systematic biases or lane-specific artifacts in Illumina or Ion Torrent data.

Example Prompts

1. "Analyze these five FASTQC reports in the current directory and generate a summary CSV, highlighting any samples that failed the per-base sequence quality check."
2. "I am running a DNA-seq pipeline for variant calling. Interpret the attached FASTQC report and let me know if the duplication rate is acceptable or if I need to re-sequence."
3. "The FASTQC results show a spike in adapter content at the end of the reads. What specific cutadapt settings should I use to clean this up for my RNA-seq experiment?"

Tips & Limitations

• Threshold Tuning: While default thresholds are scientifically sound, always consider your specific downstream application. DNA-seq for variant calling typically requires higher stringency than RNA-seq for differential expression.
• Interpretive Context: The tool identifies symptoms (e.g., poor quality); human expertise is still required to confirm the root cause (e.g., over-cycling vs. poor cluster generation).
• Data Privacy: Ensure that any FASTQC reports uploaded to the agent do not contain sensitive metadata or personally identifiable information if sharing data across shared computing environments.