Bio Genome Assembly Assembly Qc

Version Compatibility

Reference examples tested with: QUAST 5.2+, BUSCO 5.5+ (and 6.x for odb12 lineages), compleasm 0.2.6+, Merqury 1.3+, meryl 1.4+, minimap2 2.26+, Inspector 1.2+, CRAQ 1.0+, merfin 1.0+, GenomeScope2 2.0+.

Before using code patterns, verify installed versions match. If versions differ:

• CLI: <tool> --version then <tool> --help to confirm flags
• Python: pip show <package> then help(module.function) to check signatures

Results depend on inputs that outlive the binary version - record them:

• BUSCO/compleasm depend on the lineage dataset and OrthoDB generation. _odb10 (BUSCO 5) and _odb12 (BUSCO 6 default) gene sets are not comparable across the version boundary; a 99% on the shallow eukaryota_odb10 (255 genes) is a different claim from 99% on a deep clade set (5,500+).
• Merqury QV/completeness depend on the k-mer size (from best_k.sh <genome_size>, not hardcoded) and the read set used for the k-mer DB (use accurate reads; see the circularity warning below).
• NG50/NGx/auNG depend on the expected genome-size estimate (GenomeScope2 / flow cytometry / a congener).

If code throws an error, introspect the installed tool and adapt rather than retrying.

Assembly QC

"Is my genome assembly any good?" -> Measure all three orthogonal axes - contiguity, completeness, correctness - with reference-free methods, because no single number (least of all N50) is quality.

• CLI: quast.py asm.fa --large --eukaryote -o out (contiguity + reference-based structure), busco -i asm.fa -m genome -l <lineage> or compleasm run -a asm.fa -l <lineage> (gene completeness), merqury.sh reads.meryl asm.fa out (reference-free QV + k-mer completeness), inspector.py -c asm.fa -r reads.fq (reference-free structural errors)

The Single Most Important Modern Insight -- Quality Is Three Orthogonal Axes; N50 Is the Most-Gamed One

Assembly quality is three genuinely orthogonal axes - contiguity, completeness, correctness - and a single number on any one is not quality. The axes do not predict each other, and the diagnostic failure modes prove it:

• Contiguous + wrong: a single-contig "chromosome" that is three chromosomes misjoined. Perfect N50, catastrophic correctness. Only Hi-C / a same-species reference / read-discordance catches it.
• Complete + shredded: BUSCO 99%, but repeats collapsed, segmental duplications merged, intergenic space wrong. BUSCO is gene-space-only and cannot see it.
• Accurate + incomplete: QV60 over the 92% that assembled, with the hard 8% (centromeres, rDNA, satellites) simply absent. QV is silent about what is not there.

The field's historical sin is reporting contiguity alone because it is cheapest to compute and easiest to game. N50 is the most-gamed metric in genomics: it rises when sequence is thrown away (N50 is computed on what survives), when misjoins are not broken (a misjoined contig is a long contig), and when haplotigs are retained. A bigger N50 is louder, not better. Three load-bearing moves:

1. Report auN/NGx, not bare N50. auN = the area under the Nx curve = length-weighted mean contig length; it integrates the whole curve and is continuous where N50 jumps discontinuously (the small-L50 / T2T regime). NGx/auNG normalize to the expected genome size, coupling contiguity to completeness (an assembly that drops half the genome gets a great N50 but a terrible NG50). Always report contig AND scaffold N50 - if scaffold >> contig, the contiguity is glue (Ns), not sequence.
2. Default to reference-free. For a novel genome there is no trusted reference; QUAST against a divergent relative reports real inversions/SVs as "misassemblies" and real SNPs as "mismatches". Use Merqury QV (accuracy) + Inspector/CRAQ (structure) + asmgene (false dup/collapse). QUAST is the special case "I have a same-organism reference," not the default.
3. Report a Merqury QV - and never compute it on the polishing reads. QV is the reference-free accuracy standard reviewers now demand; an assembly paper with no QV is a red flag. But QV from the same reads used for polishing is circular - the polisher already made the assembly agree with those reads, so the QV measures convergence, not correctness. Build the k-mer DB from accurate, ideally independent reads (HiFi/Illumina, not noisy ONT).

Tool Taxonomy

Decision Tree by Scenario

Contiguity -- auN/NGx (not bare N50)

k8 calN50.js -L <genome_size> asm.fa       # N50/L50 + NG50/NGx + auN/auNG; -L sets genome size for NG/auNG (ships with minimap2)
quast.py asm.fa --large --eukaryote -t 16 -o quast_out   # N50/L50, GC, # contigs; NG50 only with -r or --est-ref-size; structure only if -r given

--large implies --eukaryote --min-contig 3000 --min-alignment 500 --extensive-mis-size 7000. Report contig AND scaffold N50; a scaffold N50 far above the contig N50 means the contiguity is scaffolding Ns, and every gap is a join hypothesis that could be a misassembly. NA50 (QUAST, contigs broken at misassemblies) far below N50 means the contiguity is partly fictional.

Completeness -- BUSCO / compleasm + Merqury k-mer completeness

busco -i asm.fa -m genome -l vertebrata_odb10 -o busco_out -c 16   # metaeuk predictor (default)
busco -i asm.fa -m genome --auto-lineage -o busco_out -c 16        # auto-pick if clade unknown
compleasm run -a asm.fa -l vertebrata -o compleasm_out -t 16        # miniprot-based; faster + more sensitive

Reported as C:[S,D],F,M,n. Read C, F, and M together, never C alone: high Fragmented with high Complete signals a contiguity/base-quality problem hidden behind the headline. Use the deepest applicable clade dataset (a 99% on the shallow eukaryota_odb10 ~255-gene set is trivially easy and not comparable to a deep clade set), and record the lineage + OrthoDB generation. On a high-quality assembly, BUSCO reported ~95.7% complete where compleasm reported ~99.6% on the same human genome (Huang & Li 2023) - the missing ~4% was missing from BUSCO's predictor, not the genome - so prefer compleasm on good genomes. Both share gene-space blindness: they say nothing about intergenic/repeat/regulatory sequence. Merqury k-mer completeness scores the whole genome (reliable read k-mers found in the assembly / reliable read k-mers in the reads), catching missing sequence BUSCO cannot see; it is blind to structure (a scrambled-but-present genome scores 100%).

Correctness -- Merqury QV (reference-free) and structural validation

Goal: Get a reference-free per-base accuracy (QV) plus a copy-number/false-duplication picture, then structural errors without a reference.

Approach: Build a meryl k-mer DB at the best_k.sh-derived k from accurate reads, run Merqury for QV + completeness + spectra-cn, and map raw long reads back with Inspector/CRAQ for structural errors. Refine QV with merfin where multiplicity bias matters.

best_k.sh <genome_size>                          # prints recommended k (NOT hardcoded); ~18-21 for Gbp genomes
meryl count k=21 reads.fastq output reads.meryl  # k from best_k.sh; use ACCURATE reads (HiFi/Illumina)
merqury.sh reads.meryl asm.fa out                # -> out.qv (per-scaffold + overall), out.completeness.stats, spectra-cn

inspector.py -c asm.fa -r reads.fq -o insp_out --datatype hifi -t 16   # reference-free structural + base errors
craq -g asm.fa -sms long_reads.bam -ngs short_reads.bam -o craq_out    # R-AQI/S-AQI; CRE (regional)/CSE (structural)

QV: with E = K_asm-only / K_total, per-base error P = 1 - (1 - E)^(1/k) and QV = -10*log10(P) (the ^(1/k) converts a k-mer error rate to per-base, since one wrong base breaks k overlapping k-mers). QV40 = 1 error/10 kb (the EBP/VGP floor), QV50 strong, ~QV60 = T2T-grade (1/Mb). The spectra-cn plot reads completeness and false duplication in one figure: a black "missing" peak at homozygous depth = real content absent; 2-copy k-mers under the 1-copy peak = uncollapsed haplotigs; error k-mers sit far left.

EBP/VGP standards and phased QC

The EBP minimum is 6.C.Q40: x.y.z where x = log10 of contig NG50 (6 = 1 Mb), y = scaffold level (C = chromosome-scale), z = QV (40 = <1 error/10 kb). It is literally the triad turned into a label, and the bar moves - T2T pushed the achievable frontier to ~Q60/gapless, so bragging about QV40 in 2026 is hitting the floor. Match the bar to the organism (the relaxed "5" tier, >100 kb contig NG50, exists for low-input species). For phased diploid/trio assemblies, Merqury hap-mers (parental k-mers, or Hi-C) give the switch error (local haplotype flips within a block) and hamming error (global mis-assignment fraction) - report both, and read the hap-mer blob plot (cleanly phased contigs sit on one axis).

Per-Method Failure Modes

Leading with N50 (and stopping)

Trigger: reporting a single N50 as the quality verdict. Mechanism: N50 rises on thrown-away sequence, unbroken misjoins, and retained haplotigs; it is also a single unstable order-statistic. Symptom: big N50, unstated QV/completeness/NG50. Fix: report auN/NGx + BUSCO/compleasm + Merqury QV; treat N50-only claims as untrustworthy.

QUAST against a divergent reference

Trigger: quast.py -r congener.fa on a novel genome. Mechanism: real inversions/SVs and SNPs between organism and reference are scored as "misassemblies"/"mismatches"; the count scales with divergence, not error. Symptom: "hundreds of misassemblies" on a correct assembly. Fix: use reference-free correctness (Inspector/CRAQ/Merqury); reserve QUAST structure for a same-organism reference.

QV computed on the polishing reads

Trigger: QV from the exact reads used to polish. Mechanism: the polisher made the assembly agree with those reads by construction. Symptom: impressively high QV that rose after polishing with the QV reads. Fix: build the k-mer DB from accurate, ideally independent reads; consider merfin for multiplicity-corrected QV.

High BUSCO-Duplicated read as success

Trigger: treating high BUSCO-D as "extra coverage / more complete". Mechanism: uncollapsed haplotigs (both alleles kept as separate primary contigs) vs real WGD vs split models. Symptom: D in high single digits to tens, assembly size >> GenomeScope2 estimate. Fix: triangulate size + spectra-cn 2-copy peak + asmgene false-dup; if no WGD -> purge_dups, then re-QC (watch for over-purge: size dropping below the estimate deletes real segmental duplications).

QV/BUSCO accepted on an incomplete genome

Trigger: QV60 + BUSCO 99% taken as "done". Mechanism: QV is measured on what assembled; BUSCO scores the conserved easy core only. Symptom: high accuracy and gene-completeness while 8-15% of sequence (repeats/centromeres) is absent. Fix: add Merqury k-mer completeness (whole-genome) and inspect read mapping-rate/coverage uniformity.

Quantitative Thresholds

Common Errors

References

• Gurevich A, Saveliev V, Vyahhi N, Tesler G. 2013. QUAST: quality assessment tool for genome assemblies. Bioinformatics 29:1072-1075.
• Manni M, et al. 2021. BUSCO update: novel and streamlined workflows along with broader and deeper phylogenetic coverage for scoring of eukaryotic, prokaryotic, and viral genomes. Mol Biol Evol 38:4647-4654.
• Simão FA, et al. 2015. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics 31:3210-3212.
• Huang N, Li H. 2023. compleasm: a faster and more accurate reimplementation of BUSCO. Bioinformatics 39:btad595.
• Rhie A, Walenz BP, Koren S, Phillippy AM. 2020. Merqury: reference-free quality, completeness, and phasing assessment for genome assemblies. Genome Biol 21:245.
• Formenti G, et al. 2022. Merfin: improved variant filtering, assembly evaluation and polishing via k-mer validation. Nat Methods 19:696-704.
• Chen Y, et al. 2021. Accurate long-read de novo assembly evaluation with Inspector. Genome Biol 22:312.
• Li K, et al. 2023. CRAQ: identification of errors in draft genome assemblies at single-nucleotide resolution for quality assessment and improvement. Nat Commun 14:6556.
• Ranallo-Benavidez TR, Jaron KS, Schatz MC. 2020. GenomeScope 2.0 and Smudgeplot for reference-free profiling of polyploid genomes. Nat Commun 11:1432.
• Rhie A, et al. 2021. Towards complete and error-free genome assemblies of all vertebrate species (VGP). Nature 592:737-746.
• Li H. 2020. auN: a new metric to measure assembly contiguity. Blog post (lh3.github.io); auN/asmgene tools ship in minimap2/calN50 (Li 2018 Bioinformatics 34:3094-3100).
• Guan D, et al. 2020. Identifying and removing haplotypic duplication in primary genome assemblies (purge_dups). Bioinformatics 36:2896-2898.

Related Skills

• short-read-assembly - Short-read assemblies plateau at the repeat structure; QC shows it
• long-read-assembly - Produces the contiguous-but-error-prone contigs this QC evaluates
• hifi-assembly - Phased diploid output whose false duplication and switch/hamming error this QC checks
• assembly-polishing - Merqury QV plateau is the honest stop signal; never QV on the polishing reads
• scaffolding - Validate chromosome-scale joins (Hi-C/contact map) before trusting scaffold NG50
• contamination-detection - MAG completeness/contamination (CheckM2/GUNC/MIMAG) is a separate problem
• genome-profiling - GenomeScope2 genome-size estimate that NG50/auNG/spectra-cn require
• genome-annotation/annotation-qc - Assembly-side completeness; purge haplotigs before annotating
• workflows/genome-assembly-pipeline - End-to-end QC -> assemble -> polish -> scaffold -> QC