Long-Read Quality Control
NanoPlot - Visualization
# 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
NanoPlot --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
# 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
# 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
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
NanoFilt - Alternative Filter
# 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
# 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
# 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
# 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
# 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
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}')
NanoPlot Output Files
| 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 |
Key Parameters - 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 |
Key Parameters - chopper
| 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 |
Quality Thresholds
| 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) |
Related Skills
- long-read-alignment - Align filtered reads
- sequence-io - FASTQ handling
- medaka-polishing - Polish with filtered reads