xiaohongshu
xiaohongshu
bio-genome-assembly-assembly-qc
Assess genome assembly quality using QUAST for contiguity metrics and BUSCO for completeness. Essential for evaluating assembly success and comparing assemblers. Use when evaluating assembly completeness and quality.
Full skill instructions
Evaluate genome assembly quality with contiguity metrics (QUAST) and gene completeness (BUSCO).
| Metric | Good Assembly |
|---|---|
| N50 | High (relative to genome) |
| L50 | Low |
| Contigs | Few |
| Misassemblies | 0 (with reference) |
| BUSCO Complete | >95% |
| BUSCO Duplicated | <5% (unless polyploid) |
conda install -c bioconda quast
quast.py assembly.fasta -o quast_output
quast.py assembly.fasta -r reference.fasta -o quast_output
quast.py assembly1.fa assembly2.fa assembly3.fa -o comparison
| Option | Description |
|---|---|
-o | Output directory |
-r | Reference genome |
-g | Gene annotations (GFF) |
-t | Threads |
-m | Min contig length (default: 500) |
--large | For large genomes (>100Mb) |
--fragmented | For highly fragmented assemblies |
--scaffolds | Input is scaffolds (includes N-gaps) |
quast.py assembly.fasta -r reference.fasta -g genes.gff -o quast_output
quast.py --large assembly.fasta -o quast_output -t 16
quast_output/
├── report.txt # Summary statistics
├── report.html # Interactive report
├── report.tsv # Tab-separated stats
├── icarus.html # Contig viewer
└── aligned_stats/ # If reference provided
| Metric | Description |
|---|---|
| Total length | Sum of contig lengths |
| # contigs | Number of contigs (>= min length) |
| Largest contig | Length of largest contig |
| N50 | 50% of assembly in contigs >= this length |
| N90 | 90% of assembly in contigs >= this length |
| L50 | Number of contigs comprising N50 |
| GC % | GC content |
| # misassemblies | With reference: structural errors |
| Genome fraction | With reference: % of reference covered |
conda install -c bioconda busco
busco -i assembly.fasta -m genome -l bacteria_odb10 -o busco_output
| Option | Description |
|---|---|
-i | Input assembly |
-m | Mode: genome, proteins, transcriptome |
-l | Lineage dataset |
-o | Output name |
-c | CPU threads |
--auto-lineage | Auto-detect lineage |
--offline | Use downloaded datasets only |
--list-datasets | List available lineages |
busco --list-datasets
| Lineage | Use For |
|---|---|
| bacteria_odb10 | Bacteria |
| archaea_odb10 | Archaea |
| eukaryota_odb10 | General eukaryote |
| fungi_odb10 | Fungi |
| metazoa_odb10 | Animals |
| vertebrata_odb10 | Vertebrates |
| mammalia_odb10 | Mammals |
| viridiplantae_odb10 | Plants |
| saccharomycetes_odb10 | Yeasts |
busco -i assembly.fasta -m genome --auto-lineage -o busco_output
busco_output/
├── short_summary.txt # Quick summary
├── full_table.tsv # All BUSCO results
├── missing_busco_list.tsv # Missing genes
└── busco_sequences/ # BUSCO gene sequences
C:98.5%[S:97.0%,D:1.5%],F:0.5%,M:1.0%,n:4085
C - Complete (total)
S - Single-copy
D - Duplicated
F - Fragmented
M - Missing
n - Total BUSCO groups
| Quality | Complete | Missing |
|---|---|---|
| Excellent | >95% | <2% |
| Good | >90% | <5% |
| Acceptable | >80% | <10% |
| Poor | <80% | >10% |
#!/bin/bash
set -euo pipefail
ASSEMBLY=$1
REFERENCE=${2:-}
LINEAGE=${3:-bacteria_odb10}
OUTDIR=${4:-assembly_qc}
mkdir -p $OUTDIR
echo "=== Assembly QC ==="
# QUAST
echo "Running QUAST..."
if [ -n "$REFERENCE" ]; then
quast.py $ASSEMBLY -r $REFERENCE -o ${OUTDIR}/quast -t 8
else
quast.py $ASSEMBLY -o ${OUTDIR}/quast -t 8
fi
# BUSCO
echo "Running BUSCO..."
busco -i $ASSEMBLY -m genome -l $LINEAGE -o busco_run -c 8
mv busco_run ${OUTDIR}/busco
# Summary
echo ""
echo "=== QUAST Summary ==="
cat ${OUTDIR}/quast/report.txt
echo ""
echo "=== BUSCO Summary ==="
cat ${OUTDIR}/busco/short_summary*.txt
echo ""
echo "Reports saved to $OUTDIR"
quast.py \
spades_assembly.fa \
flye_assembly.fa \
canu_assembly.fa \
-r reference.fa \
-l "SPAdes,Flye,Canu" \
-o assembly_comparison
# Run BUSCO on each assembly
for asm in spades.fa flye.fa canu.fa; do
name=$(basename $asm .fa)
busco -i $asm -m genome -l bacteria_odb10 -o busco_${name}
done
# Generate comparison plot
generate_plot.py -wd . busco_spades busco_flye busco_canu
import pandas as pd
def parse_quast(report_tsv):
'''Parse QUAST report.tsv file.'''
df = pd.read_csv(report_tsv, sep='\t', index_col=0)
return df.T
stats = parse_quast('quast_output/report.tsv')
print(f"N50: {stats['N50'].values[0]}")
print(f"Total length: {stats['Total length'].values[0]}")
print(f"# contigs: {stats['# contigs'].values[0]}")
import re
def parse_busco_summary(summary_file):
'''Parse BUSCO short summary.'''
with open(summary_file) as f:
text = f.read()
pattern = r'C:(\d+\.\d+)%\[S:(\d+\.\d+)%,D:(\d+\.\d+)%\],F:(\d+\.\d+)%,M:(\d+\.\d+)%,n:(\d+)'
match = re.search(pattern, text)
if match:
return {
'complete': float(match.group(1)),
'single': float(match.group(2)),
'duplicated': float(match.group(3)),
'fragmented': float(match.group(4)),
'missing': float(match.group(5)),
'total': int(match.group(6))
}
return None
result = parse_busco_summary('busco_output/short_summary.txt')
print(f"Complete: {result['complete']}%")
metaquast.py metagenome_assembly.fa -o metaquast_output -t 16
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