bio-longread-qc

Quality control for long-read sequencing data using NanoPlot, NanoStat, and chopper. Generate QC reports, filter reads by length and quality, and visualize read characteristics. Use when assessing ONT or PacBio run quality or filtering reads before assembly or alignment.

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Repository: majiayu000/claude-skill-registry
Letzte Quellaktivität: 23. Juni 2026 um 12:15
Erkannte Sprache von SKILL.md: Englisch
Sterne: 543
Forks: 85

Installationsoptionen

Standardmäßig ist der Prompt ausgewählt, der zuerst die Quelle prüft. Sie können zu einem direkten Befehl wechseln oder eine lokale Kopie herunterladen.

Mit Codex oder Claude installieren Kopieren Sie diesen Prompt, fügen Sie ihn in Codex, Claude oder einen anderen Assistant ein und lassen Sie die Skill-Seite prüfen und installieren.

Ein direkter Befehl überspringt den Prüf-Prompt. Prüfen Sie die Quelle, bevor Sie ihn ausführen.

npx skills add https://github.com/majiayu000/claude-skill-registry --skill bio-longread-qc

Der Befehl bleibt in einer Zeile. Scrollen Sie horizontal, um ihn vor dem Kopieren vollständig zu prüfen.

Sie bevorzugen eine lokale Kopie? Laden Sie die Dateien herunter, die SkillsMP derzeit vorliegen.

Quelldateien prüfen

Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.

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2 Dateien

SKILL.md

Quellanweisungen · Schreibgeschützte Vorschau

Zurück zur Suche Zurück zur Installation

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Alle aus diesem Repository ansehen

# Quick statistics (no plots)
NanoStat --fastq reads.fastq.gz --threads 4

# From BAM
NanoStat --bam aligned.bam --threads 4

# Output to file
NanoStat --fastq reads.fastq.gz --threads 4 > qc_stats.txt

# Filter by length and quality
gunzip -c reads.fastq.gz | chopper -q 10 -l 1000 | gzip > filtered.fastq.gz

# Quality >= 10, length >= 1000bp

gunzip -c reads.fastq.gz | chopper \
    --quality 10 \                 # Min quality
    --minlength 1000 \             # Min length
    --maxlength 50000 \            # Max length
    --headcrop 50 \                # Remove from start
    --tailcrop 50 \                # Remove from end
    --threads 4 \
    | gzip > filtered.fastq.gz

# Filter with NanoFilt
gunzip -c reads.fastq.gz | NanoFilt -q 10 -l 1000 | gzip > filtered.fastq.gz

# With more options
gunzip -c reads.fastq.gz | NanoFilt \
    --quality 10 \
    --length 1000 \
    --maxlength 50000 \
    --headcrop 50 \
    | gzip > filtered.fastq.gz

# Trim adapters
porechop -i reads.fastq.gz -o trimmed.fastq.gz --threads 8

# With barcode splitting
porechop -i reads.fastq.gz -b output_dir/ --threads 8

# Quick summary with seqkit
seqkit stats reads.fastq.gz

# Detailed stats
seqkit stats -a reads.fastq.gz

# Watch stats during basecalling
seqkit watch --fields ReadLen,MeanQual reads.fastq.gz

# Generate QC report from sequencing_summary.txt
pycoQC -f sequencing_summary.txt -o pycoqc_report.html

# With BAM for alignment stats
pycoQC -f sequencing_summary.txt -a aligned.bam -o pycoqc_report.html

# With seqkit
seqkit stats -a reads.fastq.gz | grep N50

# Manual calculation
seqkit fx2tab -l reads.fastq.gz | cut -f 2 | sort -rn | \
    awk '{sum+=$1; len[NR]=$1} END {
        target=sum/2; cumsum=0;
        for(i=1; i<=NR; i++) {
            cumsum+=len[i];
            if(cumsum>=target) {print "N50:", len[i]; break}
        }
    }'

import numpy as np
from Bio import SeqIO

lengths = []
qualities = []

for record in SeqIO.parse('reads.fastq', 'fastq'):
    lengths.append(len(record))
    qualities.append(np.mean(record.letter_annotations['phred_quality']))

print(f'Total reads: {len(lengths)}')
print(f'Total bases: {sum(lengths):,}')
print(f'Mean length: {np.mean(lengths):.0f}')
print(f'Median length: {np.median(lengths):.0f}')
print(f'Mean quality: {np.mean(qualities):.1f}')

File	Description
NanoStats.txt	Summary statistics
NanoPlot-report.html	Interactive report
LengthvsQualityScatterPlot	Length vs Q plot
WeightedHistogramReadlength	Read length distribution
Yield_By_Length	Cumulative yield

name	bio-longread-qc
description	Quality control for long-read sequencing data using NanoPlot, NanoStat, and chopper. Generate QC reports, filter reads by length and quality, and visualize read characteristics. Use when assessing ONT or PacBio run quality or filtering reads before assembly or alignment.
tool_type	cli
primary_tool	nanoplot

name	bio-longread-qc
description	Quality control for long-read sequencing data using NanoPlot, NanoStat, and chopper. Generate QC reports, filter reads by length and quality, and visualize read characteristics. Use when assessing ONT or PacBio run quality or filtering reads before assembly or alignment.
tool_type	cli
primary_tool	nanoplot

Parameter	Description
--fastq	Input FASTQ
--bam	Input BAM
--summary	Sequencing summary
-o	Output directory
-t	Threads
--N50	Show N50 line
--plots	Plot types
--format	Output formats

Q Score	Accuracy	Typical Use
Q7	~80%	Very low quality
Q10	~90%	Basic filtering
Q15	~97%	Moderate filtering
Q20	~99%	High quality (SUP)
Q30	~99.9%	Very high (HiFi)

bio-longread-qc

Installationsoptionen

Quelldateien prüfen

Long-Read Quality Control

NanoPlot - Visualization

NanoPlot - Common Options

NanoStat - Statistics Only

Long-Read Quality Control

NanoPlot - Visualization

NanoPlot - Common Options

NanoStat - Statistics Only

chopper - Filter Reads

chopper - Common Options

NanoFilt - Alternative Filter

Porechop - Adapter Trimming

Generate Summary Statistics

PycoQC - From Basecalling

Calculate N50

Parse FASTQ Quality in Python

NanoPlot Output Files

Key Parameters - NanoPlot

Key Parameters - chopper

Quality Thresholds

Related Skills

Parameter	Default	Description
-q	0	Min quality
-l	0	Min length
--maxlength	inf	Max length
--headcrop	0	Trim from start
--tailcrop	0	Trim from end
-t	4	Threads

bio-longread-qc

Quellinformationen

Installationsoptionen

Quelldateien prüfen

Mehr aus diesem Repository

Mehr aus diesem Repository

Long-Read Quality Control

NanoPlot - Visualization

NanoPlot - Common Options

NanoStat - Statistics Only

Long-Read Quality Control

NanoPlot - Visualization

NanoPlot - Common Options

NanoStat - Statistics Only

chopper - Filter Reads

chopper - Common Options

NanoFilt - Alternative Filter

Porechop - Adapter Trimming

Generate Summary Statistics

PycoQC - From Basecalling

Calculate N50

Parse FASTQ Quality in Python

NanoPlot Output Files

Key Parameters - NanoPlot

Key Parameters - chopper

Quality Thresholds

Related Skills