FASTQ Preprocessing with fastp

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Preprocesses Illumina FASTQ sequencing reads with automated adapter trimming, quality filtering, and interactive QC reporting in a single high-speed pass.

FASTQ Preprocessing with fastp guides Claude Code in executing ultra-fast quality control and adapter trimming for high-throughput sequencing data across RNA-seq, WGS, WES, ChIP-seq, and ATAC-seq pipelines. Operating 3–10x faster than traditional tools like Trim Galore and Trimmomatic, fastp automatically detects Illumina adapters via paired-end overlaps, repairs mismatched base calls in overlap regions, trims polyX/polyA tails, and applies rigorous Phred-score quality and length filtering. The skill provides interactive interview templates, ready-to-run shell pipelines, and Python parsing scripts for both HTML and machine-readable JSON QC outputs to enforce automated quality gates prior to alignment with STAR, BWA-MEM2, or Salmon.

主要功能

01382 GitHub stars
02Automatic adapter detection and base correction via paired-end read overlap analysis
03Comprehensive quality filtering by Phred score, minimum length, and low-complexity thresholds
04Specialized polyA/polyX tail trimming tailored for 3′-enriched RNA-seq protocols
05Dual HTML and JSON QC report generation in a single multi-threaded pass
06Batch processing automation with MultiQC aggregation and Python quality gates

使用场景

01Preprocessing raw paired-end or single-end Illumina reads before running STAR or BWA-MEM2 alignment
02Trimming polyA tails and filtering low-quality bases from QuantSeq or Smart-seq RNA-seq datasets
03Automating bioinformatics QC pipelines with programmatic JSON metric parsing and MultiQC reporting