fastp-fastq-preprocessing
All-in-one FASTQ QC and adapter trimming. Auto-detects Illumina adapters, filters low-quality reads, corrects paired-end overlaps, emits HTML+JSON QC in one pass. 3-10x faster than Trim Galore/Trimmomatic. First step before STAR, BWA-MEM2, or Salmon.
npx skills add BioTender-max/awesome-bio-agent-skills --skill fastp-fastq-preprocessing --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# fastp — Fast FASTQ Quality Control and Adapter Trimming ## Overview fastp performs adapter trimming, quality filtering, and QC reporting for Illumina FASTQ files in a single multi-threaded pass. It automatically detects adapter sequences from paired-end read overlaps — eliminating the need to specify adapters manually. fastp corrects mismatches in paired-end overlap regions, filters reads by quality score and length, removes polyX tails (polyA for RNA-seq), and generates interactive HTML and machine-readable JSON QC reports. Being 3–10× faster than Trim Galore and Trimmomatic while providing comparable or better results, fastp has become the standard preprocessing step before alignment in WGS, RNA-seq, and ChIP-seq pipelines. ## When to Use - Trimming Illumina adapters and low-quality bases before alignment in any NGS pipeline (RNA-seq, WGS, WES, ChIP-seq, ATAC-seq) - Generating per-sample QC reports (HTML + JSON) as the first step of a pipeline, before MultiQC aggregation - Processing paired-end reads where adapter auto-detection from overlap is preferred over manual adapter specification - Removing polyA tails from RNA-seq reads from 3′ end-enriched protocols (Smart-seq, QuantS
- Overview
- When to Use
- Prerequisites
- Quick Start
- Workflow
- Step 1: Single-End Adapter Trimming
- Step 2: Paired-End Adapter Trimming
- Step 3: Quality Filtering and Read Length Trimming
- Step 4: RNA-seq polyA Tail Removal
- Step 5: Parse QC Report JSON for Pipeline Monitoring
- Step 6: Batch Preprocessing Pipeline
- Key Parameters
- Common Recipes
- Recipe 1: Integrate fastp into a Snakemake Pipeline
Install with conda conda install -c bioconda fastp Or download pre-compiled binary (Linux) wget https://github.com/OpenGene/fastp/releases/download/v0.24.0/fastp chmod +x fastp fastp 0.24.0 Verify fastp --version Paired-end adapter trimming with QC report fastp \
What does the fastp-fastq-preprocessing skill do?
All-in-one FASTQ QC and adapter trimming. Auto-detects Illumina adapters, filters low-quality reads, corrects paired-end overlaps, emits HTML+JSON QC in one pass. 3-10x faster than Trim Galore/Trimmomatic. First step before STAR, BWA-MEM2, or Salmon.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill fastp-fastq-preprocessing --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.