Bio Read Qc Fastp Workflow

What it does

When your agent uses it

• Preprocessing bulk Illumina data and wanting one fast tool instead of separate Cutadapt

Example prompts

• “/bio-read-qc-fastp-workflow”

Requirements

• Python 3
• A Bash shell

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

1. 1fastp trims paired-end adapters by OVERLAP ANALYSIS, needing no adapter sequence at all. It aligns R1 against the reverse complement of…
2. 2dedup is SEQUENCE-identity deduplication at the FASTQ level -- no coordinates, no UMI -- so it removes BIOLOGICAL duplicates too. It…
3. 3Poly-G trimming auto-enables for 2-color instruments (NextSeq/NovaSeq) from the machine ID, because G is the no-signal call. Leave it on…

What it can do on your machine

Read from SKILL.md and the folder at commit d91ed3d. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Ships script files (Shell), which the agent can run.

  Shell commands in SKILL.md call:

  • pip

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  No URLs in SKILL.md. Its commands use pip, which can reach the network depending on how they are called.

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Bio Read Qc Fastp Workflow loads about 2.3k tokens when it runs. Until then it costs about 125 tokens; SKILL.md has 740 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~125

When it runs · the whole SKILL.md, loaded when a task matches

~2.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from GPTomics/bioSkills at commit d91ed3d, republished under its MIT licence (© GPTomics). 740 words, ~2,348 tokens.

name

bio-read-qc-fastp-workflow

description

Runs all-in-one FASTQ preprocessing with fastp in a single pass - adapter trimming via paired-end overlap analysis, quality/length filtering, 2-color poly-G removal, base correction, optional dedup/UMI/merge, and HTML/JSON reports. Use when preprocessing bulk Illumina data and wanting one fast tool instead of separate Cutadapt, Trimmomatic, and FastQC steps. For precise small-RNA/amplicon adapters use adapter-trimming; for molecule-accurate UMI dedup use umi-processing.

tool_type

cli

primary_tool

fastp

# Single-end and paired-end basics
fastp -i in.fq.gz -o out.fq.gz
fastp -i R1.fq.gz -I R2.fq.gz -o c_R1.fq.gz -O c_R2.fq.gz

# Adapter: PE overlap is automatic; --detect_adapter_for_pe ADDS sequence-based detection on top
fastp -i R1.fq.gz -I R2.fq.gz -o c_R1.fq.gz -O c_R2.fq.gz --detect_adapter_for_pe
# Manual adapter sequences (SE auto-detects from data by default)
fastp -i in.fq.gz -o out.fq.gz --adapter_sequence AGATCGGAAGAGCACACGTCTGAACTCCAGTCA

# Quality FILTER (per-read): base <Q20 unqualified; drop if >40% unqualified or >5 Ns
fastp -i in.fq.gz -o out.fq.gz -q 20 -u 40 -n 5
# Quality TRIM (sliding window from 3', SLIDINGWINDOW analogue) + length gate
fastp -i in.fq.gz -o out.fq.gz --cut_right --cut_window_size 4 --cut_mean_quality 20 -l 36

# 2-color poly-G (auto for NextSeq/NovaSeq); poly-X for 3' poly-A etc.
fastp -i in.fq.gz -o out.fq.gz --trim_poly_g          # --poly_g_min_len 10 default
fastp -i in.fq.gz -o out.fq.gz --trim_poly_x

# Overlap base correction (PE only; high-Q mate fixes low-Q base)
fastp -i R1.fq.gz -I R2.fq.gz -o c_R1.fq.gz -O c_R2.fq.gz --correction

# Merge overlapping pairs (short inserts: cfDNA, small-RNA, aDNA). Produces THREE streams:
# the merged file is single-end (full insert) and un_R1/un_R2 stay paired -- align them separately
# (merged as SE, un_R1/un_R2 as PE) and combine the BAMs.
fastp -i R1.fq.gz -I R2.fq.gz --merge --merged_out merged.fq.gz -o un_R1.fq.gz -O un_R2.fq.gz

# UMI extraction: fastp moves the inline UMI out of the read before trimming; molecule-accurate
# dedup/consensus still happens AFTER alignment (umi_tools/fgbio), not in fastp
fastp -i R1.fq.gz -I R2.fq.gz -o c_R1.fq.gz -O c_R2.fq.gz --umi --umi_loc read1 --umi_len 8

# Standard Illumina PE (4-color: HiSeq/MiSeq)
fastp -i raw_R1.fq.gz -I raw_R2.fq.gz -o clean_R1.fq.gz -O clean_R2.fq.gz \
      --detect_adapter_for_pe --cut_right --cut_window_size 4 --cut_mean_quality 20 \
      -q 20 -l 36 -w 8 -h sample.html -j sample.json

# NovaSeq / NextSeq (2-color): add poly-G (auto, but explicit for clarity)
fastp -i raw_R1.fq.gz -I raw_R2.fq.gz -o clean_R1.fq.gz -O clean_R2.fq.gz \
      --detect_adapter_for_pe --trim_poly_g \
      --cut_right --cut_window_size 4 --cut_mean_quality 20 -q 20 -l 36 -w 8 \
      -h sample.html -j sample.json

# RNA-seq: light trim only (aligner soft-clips; do NOT --dedup), longer min length
fastp -i raw_R1.fq.gz -I raw_R2.fq.gz -o clean_R1.fq.gz -O clean_R2.fq.gz \
      --detect_adapter_for_pe -q 20 -l 50 -w 8 -h sample.html -j sample.json

import json

with open('sample.json') as f:
    report = json.load(f)

after = report['summary']['after_filtering']
print(f"reads kept: {after['total_reads']}, Q30: {after['q30_rate']:.2%}")
print(f"duplication: {report['duplication']['rate']:.2%}")    # diagnostic only -- do not auto-dedup

© GPTomics, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files in read-qc/fastp-workflow of GPTomics/bioSkills.

• SKILL.md
• examples/fastp_pipeline.sh
• usage-guide.md

Open the folder on GitHubat commit d91ed3d

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in GPTomics/bioSkills, which our catalogue first saw on October 7, 2026.

• PKU-YuanGroup/OpenAI4Sskills/bioskills/bio-read-qc-fastp-workflow