---

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

Long-Read Quality Control

NanoPlot - Visualization

Copy# From FASTQ
NanoPlot --fastq reads.fastq.gz -o nanoplot_output -t 4

# From BAM
NanoPlot --bam aligned.bam -o nanoplot_output -t 4

# From sequencing summary (fastest)
NanoPlot --summary sequencing_summary.txt -o nanoplot_output

NanoPlot - Common Options

CopyNanoPlot --fastq reads.fastq.gz \
    -o nanoplot_output \
    -t 8 \
    --N50 \                        # Show N50 in plots
    --title "Sample QC" \
    --plots hex dot \              # Plot types
    --format png pdf \             # Output formats
    --color darkblue \
    --maxlength 50000 \            # Max length for plots
    --minlength 500                # Min length for plots

NanoStat - Statistics Only

Copy# 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

chopper - Filter Reads

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

# Quality >= 10, length >= 1000bp

chopper - Common Options

Copygunzip -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

NanoFilt - Alternative Filter

Copy# 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

Porechop - Adapter Trimming

Copy# 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

Generate Summary Statistics

Copy# 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

PycoQC - From Basecalling

Copy# 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

Calculate N50

Copy# 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}
        }
    }'

Parse FASTQ Quality in Python

Copyimport 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}')

NanoPlot Output Files

Key Parameters - NanoPlot

Key Parameters - chopper

Quality Thresholds

Related Skills

• long-read-alignment - Align filtered reads
• sequence-io - FASTQ handling
• medaka-polishing - Polish with filtered reads