Agent skill · Code Review & Quality

bio-fastq-quality

Work with FASTQ quality scores using Biopython. Use when analyzing read quality, filtering by quality, trimming low-quality bases, or generating quality reports.

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill fastq-quality-gptomics-bioskills --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 7 KB
Bundled scripts: none
Path: skills/ai-ml/fastq-quality-gptomics-bioskills/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# FASTQ Quality Scores Analyze and manipulate FASTQ quality scores using Biopython. ## Required Imports ```python from Bio import SeqIO from Bio.Seq import Seq ``` ## Accessing Quality Scores Quality scores are stored in `letter_annotations['phred_quality']` as a list of integers. ```python for record in SeqIO.parse('reads.fastq', 'fastq'): qualities = record.letter_annotations['phred_quality'] print(record.id, qualities[:10]) # First 10 quality scores ``` ## Quality Score Basics | Phred Score | Error Probability | Accuracy | |-------------|-------------------|----------| | 10 | 1 in 10 | 90% | | 20 | 1 in 100 | 99% | | 30 | 1 in 1000 | 99.9% | | 40 | 1 in 10000 | 99.99% | ## Code Patterns ### Calculate Average Quality per Read ```python for record in SeqIO.parse('reads.fastq', 'fastq'): quals = record.letter_annotations['phred_quality'] avg_qual = sum(quals) / len(quals) print(f'{record.id}: {avg_qual:.1f}') ``` ### Filter Reads by Mean Quality ```python def high_quality_reads(records, min_avg_qual=20): for record in records: quals = record.letter_annotations['phred_quality'] if sum(quals) / len(quals) >= min_avg_qual: yield record records = SeqIO.parse('reads.fastq', 'fastq') goo

What's inside
Steps it walks through
  1. Required Imports
  2. Accessing Quality Scores
  3. Quality Score Basics
  4. Code Patterns
  5. Calculate Average Quality per Read
  6. Filter Reads by Mean Quality
  7. Filter by Minimum Quality at Any Position
  8. Trim Low-Quality Ends (3' Trimming)
  9. Sliding Window Quality Trim
  10. Quality Statistics Summary
  11. Per-Position Quality Profile
  12. Count Reads by Quality Threshold
  13. Remove N Bases and Low Quality Together
  14. FASTQ Format Variants
Ships with 1 file
  • metadata.json
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About this skill
What does the bio-fastq-quality skill do?

Work with FASTQ quality scores using Biopython. Use when analyzing read quality, filtering by quality, trimming low-quality bases, or generating quality reports.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill fastq-quality-gptomics-bioskills --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 majiayu000/claude-skill-registry, a repository with 534 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.

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