bio-genome-assembly-scaffolding

name	bio-genome-assembly-scaffolding
description	Orders and orients assembled contigs into chromosome-scale scaffolds from long-range linking data, inserting N-gap spacers (adds no sequence). Covers Hi-C/Omni-C scaffolding (YaHS, SALSA2, 3D-DNA/Juicer), Hi-C read-mapping prerequisites (map each end separately, no mate rescue, dedup, enzyme-aware), reading the contact map for misjoins/inversions/false-duplications, manual curation in Juicebox/PretextView (the VGP/DToL standard), reference-guided scaffolding (RagTag) and its karyotype-erasure hazard, genetic-map (ALLMAPS) and Bionano optical-map integration, chimera-breaking before scaffolding, gap-filling, and telomere/contig-vs-scaffold-N50 QC (tidk). Use when turning contigs into chromosomes with Hi-C, integrating a linkage map or optical map, choosing a scaffolder by available linking data, or judging whether a chromosome-scale assembly is trustworthy.
tool_type	cli
primary_tool	YaHS

Version Compatibility

Reference examples tested with: YaHS 1.2+, SALSA2 2.3+, juicer_tools 1.22/2.0+, bwa 0.7.17+, chromap 0.2+, samtools 1.19+, RagTag 2.1+, tidk 0.2.3+, seqkit 2.6+.

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

• CLI: <tool> --version then <tool> --help to confirm flags

hifiasm output filenames and YaHS/SALSA2 enzyme and resolution defaults have changed across releases; confirm output names and -e/-r behaviour against the installed version. The Hi-C-mapping flag set (bwa mem -5SP vs the Arima/VGP per-end pipeline) varies by vendor (Arima, Dovetail/Omni-C, Phase Genomics) - check the current mapping guide before pasting flags. If a command errors, introspect the tool and adapt rather than retrying.

Genome Scaffolding

"Turn my contigs into chromosomes" -> Order and orient contigs by long-range linking signal, insert N-gap spacers, then curate the contact map - scaffolding adds no sequence, so the output is a draft chromosome structure, not finished sequence.

• CLI: yahs contigs.fa hic_to_contigs.bam (Hi-C default), run_pipeline.py -a contigs.fa -b sorted.bed -m yes (SALSA2), ragtag.py scaffold ref.fa contigs.fa (reference-guided), allmaps path (linkage maps)

The Single Most Important Modern Insight -- Automated Scaffolding Produces a Draft; the Genome Is Trustworthy Only After Manual Curation of the Contact Map

YaHS finishes in minutes and emits a file literally named _scaffolds_final.agp. It is not final. Hi-C scaffolding is a contact-frequency inference - it orders/orients contigs by the polymer-physics signal that contact frequency decays with 1D distance - and it is error-prone exactly at the joins. Every reference-grade pipeline (VGP, Darwin Tree of Life, Earth BioGenome) treats the automated AGP as a first pass that a human curator then corrects in PretextView or Juicebox: breaking misjoins, flipping inversions, removing false duplications, assigning chromosomes by eye. Howe 2021 quantified the hidden labor across 111 VGP/DToL assemblies: on average 221 interventions per Gb (67 breaks, 105 joins, 49 false-duplication removals). Three load-bearing consequences:

1. The contact map is the QC, not a decoration. A correct chromosome shows one bright diagonal with smooth off-diagonal decay; off-diagonal blocks, anti-diagonal "bowties," and bleeding between chromosomes are errors to inspect and break (see Reading the Contact Map). An assembly paper whose methods say "scaffolded with [tool]" but never mention curation/Juicebox/PretextView is shipping a draft - downgrade any claim that depends on large-scale order (synteny, fusions, structural variants).

2. Scaffold N50 is not contig N50, and conflating them is the classic reviewer catch. Scaffolding inserts runs of N (estimated, often arbitrary length) and adds zero sequence. A genome can post "scaffold N50 = 60 Mb, chromosome-scale!" while its contig N50 is 200 kb - the contiguity is borne by gaps, not finished sequence. Always report contig N50, scaffold N50, gap count, and total N bases separately.

3. Reordering cannot rescue a bad contig. Scaffolders take contigs as given; a chimeric contig drags the wrong sequence into the wrong chromosome. Chimeras must be broken before scaffolding (see Chimera-Breaking).

Linking-Data Modality Taxonomy

Modality	How it links	Scale	Status
Hi-C / Omni-C	proximity ligation; contact frequency ~ 1/(1D distance)	chromosome-scale	Dominant modern method. Omni-C is enzyme-free/sequence-agnostic; Arima uses fixed enzyme motifs
Bionano optical maps (DLS)	labeled motif patterns aligned to in-silico contig maps	megabase	Resolves large SVs and bridges complex repeats; separate instrument + library (cost decision)
10x linked reads	barcoded short reads from one long molecule	~10-100 kb	DISCONTINUED by 10x (2020). Legacy data only; Tigmint/ARCS still run, no new data
Genetic / linkage maps	marker recombination order = chromosome order	chromosome-scale, low resolution	ALLMAPS integrates multiple maps; orthogonal validation of Hi-C
Reference (homology)	align contigs to a related genome, copy its order	as good as synteny	RagTag. Fast, but imposes the reference's karyotype - see hazard below
Long reads as linkers	k-mer pairs spanning junctions	read length	LINKS; mostly superseded by assembling with the long reads directly
Mate-pair / jumping	large-insert paired short reads	2-40 kb	Legacy (SSPACE); chimeric-insert artifacts; never recommend today

Decision Tree by Available Linking Data

Available linking data	Use	Why
Hi-C/Omni-C, want fast contiguous default	YaHS	community default; fast, high N90, AGP + Juicebox outputs in one command
Hi-C, want graph-aware conservative joins + input-error correction	SALSA2 -m yes (-g graph.gfa)	iterative; breaks chimeric input; uses assembly graph to avoid orientation errors
Hi-C, interactive curation central to workflow	3D-DNA + Juicer + Juicebox (JBAT)	the Aiden-lab .assembly <-> Juicebox round-trip is built around hand-editing
Hi-C, vertebrate/reference-grade	YaHS or SALSA2 -> PretextView/JBAT curation	VGP/DToL standard: automate then curate
Diploid, Hi-C, want both haplotypes as chromosomes	hifiasm --h1/--h2 to PHASE first, then YaHS to SCAFFOLD each haplotype	same Hi-C, two jobs - phasing picks the homolog, scaffolding orders along it (see Phasing vs Scaffolding)
Closely related reference, karyotype NOT a question	RagTag correct then scaffold	homology ordering in minutes - but never if karyotype is the biology
One or more genetic/linkage maps	ALLMAPS	integrates multiple maps; robust to marker errors; validates/anchors Hi-C
Bionano optical maps + sequence assembly	Bionano Solve hybrid scaffold (before Hi-C)	megabase maps bridge complex repeats and large SVs
10x linked reads (legacy data)	Tigmint (break) -> ARCS/ARKS (link)	break misassemblies first; no new 10x data exists
Contigs not yet QC'd / haplotigs present	-> assembly-qc, purge_dups	scaffolding haplotigs strings them up as fake chromosomes
Hi-C contact map for TADs/loops, not chromosomes	-> hi-c-analysis/matrix-operations	different use of the same assay

Modern reference-grade recipe (vertebrate/eukaryote): HiFi -> hifiasm contigs -> (optional Bionano hybrid scaffold) -> Hi-C scaffold (YaHS/SALSA2) -> manual curation in PretextView/JBAT -> gap-fill (TGS-GapCloser) -> QC (tidk telomeres, contact-map diagonal, contig-vs-scaffold N50).

Hi-C Read Mapping (the step people botch)

Hi-C reads are not a normal paired-end library: the two ends come from different genomic loci ligated together, so standard PE proper-pair/insert-size logic mis-handles them.

# Map each end SEPARATELY with no mate rescue/pairing; -5 reports the 5' (junction) portion as primary.
bwa index contigs.fa
bwa mem -5SP -T0 -t 16 contigs.fa hic_R1.fq.gz hic_R2.fq.gz | \
    samtools view -@ 8 -b - > aligned.bam
# Mandatory: mark/remove PCR + optical duplicates (Hi-C is duplicate-rich) before scaffolding.
samtools sort -@ 8 -n aligned.bam | samtools fixmate -m - - | \
    samtools sort -@ 8 - | samtools markdup -@ 8 - hic_to_contigs.bam
samtools index hic_to_contigs.bam

• Each end separately, no mate rescue (-5SP): -5 = 5' portion of a chimeric junction read as primary; -S/-P skip mate rescue and pairing. The Arima/VGP per-end pipeline (bwa mem on R1 and R2 independently, filter_five_end.pl, two_read_bam_combiner.pl) is the higher-fidelity equivalent.
• MAPQ filter at scaffolding (YaHS -q, SALSA2 reads MAPQ) to drop repeat-ambiguous reads.
• Enzyme awareness: Arima/Dovetail-DpnII cut at fixed motifs (GATC); the scaffolder uses -e to model legitimate read starts. Omni-C / DNase Hi-C is enzyme-free -> omit -e in YaHS, use -e DNASE in SALSA2.
• chromap (Zhang 2021 Nat Commun 12:6566) is the fast modern alternative: chromap --preset hic -r contigs.fa -x index -1 R1 -2 R2 ... aligns + dedups Hi-C ~10x faster; YaHS accepts its output.

YaHS (the current default)

samtools faidx contigs.fa
# Enzyme: -e GATC (DpnII/Dovetail), -e GATC,GANTC (Arima 2-enzyme); OMIT -e for Omni-C/enzyme-free.
yahs -e GATC -o out contigs.fa hic_to_contigs.bam
# Outputs: out_scaffolds_final.agp + out_scaffolds_final.fa, intermediate out_rNN.agp, out.bin
# Contig error-correction is ON by default (--no-contig-ec to disable; usually a mistake to disable).

# Juicebox prep for curation (.hic + .assembly to load in JBAT):
# NOTE: `juicer` here is the small utility BUNDLED with YaHS (operates on the .bin), NOT Aiden-lab Juicer;
# `juicer_tools.jar` below IS the separate Aiden-lab jar. Do not confuse the two.
juicer pre -a -o out_JBAT out.bin out_scaffolds_final.agp contigs.fa.fai 2>tmp_assembly.log
java -Xmx48G -jar juicer_tools.jar pre out_JBAT.txt out_JBAT.hic <(cat tmp_assembly.log | grep PRE_C_SIZE | awk '{print $2" "$3}')
# After hand-editing in Juicebox, export out_JBAT.review.assembly, then:
juicer post -o out_curated out_JBAT.review.assembly out_JBAT.liftover.agp contigs.fa

YaHS also accepts a BED (bamToBed) or PA5/pairs input. The _scaffolds_final.agp is the editable, reviewable object - curation edits the AGP, then regenerates FASTA. --telo-motif lets YaHS use telomere signal during scaffolding.

SALSA2 (graph-aware, iterative, breaks chimeras)

bamToBed -i aligned.bam > alignment.bed
sort -k4 alignment.bed > sorted.bed                 # MUST sort by read name (column 4)
python run_pipeline.py -a contigs.fa -l contigs.fa.fai -b sorted.bed \
       -e GATC -o salsa_out -m yes -g contigs_graph.gfa -p yes
# -e DNASE for Omni-C/enzyme-free; -m yes enables input-error (chimera) correction; -p yes writes AGP+FASTA per iteration

The signature -m yes step breaks input contigs where the Hi-C signal contradicts the assembler's join before scaffolding. Assembly headers must not contain :. -i sets iterations (default 3), -c min contig length (default 1000).

Reference-Guided Scaffolding (RagTag) -- Power and Peril

ragtag.py correct ref.fa contigs.fa                 # break query at putative misassemblies vs reference FIRST
ragtag.py scaffold ref.fa ragtag_output/ragtag.correct.fasta -t 16   # order/orient by homology (minimap2 default)
# Outputs ragtag.scaffold.agp + .fasta; inserts 100 bp N gaps by default; -C collapses unplaced into chr0.

The peril (load-bearing): RagTag orders contigs to match the reference, so by construction the output looks like the reference. Every real biological rearrangement that distinguishes the target organism - a chromosome fusion, fission, translocation, or inversion polymorphism - is silently erased and replaced by the reference's structure. Never reference-scaffold a genome whose karyotype or large-scale structure is a biological question - the pipeline "discovers" the reference's karyotype because it was imposed (this has happened in the literature). Acceptable uses: a structurally conserved close relative needing only a coordinate system for gene content; a scaffold hypothesis to then test/correct against Hi-C (ragtag.py merge -b hic.bam lets Hi-C arbitrate). On a genome with interesting structure the honest move is Hi-C + curation, full stop.

Genetic/Linkage Maps (ALLMAPS) and Optical Maps (Bionano)

ALLMAPS (Tang 2015 Genome Biol 16:3) integrates one or more genetic maps to order/orient scaffolds: allmaps merge map1.csv map2.csv -o maps.bed then allmaps path maps.bed contigs.fa. It is the gold standard for validating chromosome assignment and for species where Hi-C is hard; weight multiple maps by quality. Bionano Solve hybrid scaffolding (no journal paper; cite the Bionano Solve Theory of Operation: Hybrid Scaffold technical document) aligns DLS optical maps to in-silico contig maps, resolves conflicts, and merges into hybrid scaffolds - run it before Hi-C on large/repetitive genomes where megabase maps bridge repeat arrays Hi-C fumbles. The decision is economic (separate instrument + library), not purely technical.

Reading the Contact Map (the skill nobody writes down)

The map displays its own errors to a trained eye - render with PretextMap -> PretextView (interactive, emits a curated AGP), PretextSnapshot (static PNG), or Juicebox/JBAT.

• Correct chromosome: one bright diagonal, contacts decaying smoothly off-diagonal; inter-chromosome space dim and uniform.
• Misjoin: the diagonal breaks - signal jumps off-diagonal into a separate block at the junction (two diagonals stitched at a corner). Break it.
• Inversion: an anti-diagonal "bowtie"/butterfly - the gradient runs backwards through the segment. The most common curation fix once recognized; flip it.
• Translocation / wrong assignment: off-diagonal bright blocks bleeding between what should be separate chromosomes.
• False duplication (leaked haplotig): a faint off-diagonal stripe parallel to the diagonal contacting the same neighborhood. Remove it (49 of the 221 interventions/Gb).
• Hardest judgment: the map is noisy near the diagonal even when correct. A real weak join is faint but coherent with the right decay shape; mapping noise is structureless speckle. Treat ambiguous near-diagonal signal as a flag to inspect, not a number to trust.

Chimera-Breaking, Gap-Filling, and Phasing-vs-Scaffolding

• Break, then scaffold: SALSA2 -m yes and YaHS default contig-EC break chimeric input where Hi-C contradicts the join; Tigmint (Jackman 2018 BMC Bioinformatics 19:393) breaks before ARCS for linked reads; RagTag correct for the reference-based version. Disabling these to "preserve the assembly" is a common self-inflicted wound.
• Gap-filling is a SEPARATE downstream step that replaces N-runs with real sequence by bridging long reads across the gap (TGS-GapCloser; LR_Gapcloser). Gaps sit at repeats (that is why the assembler stopped there), so a read can bridge into the wrong repeat copy and insert locally-plausible but globally-wrong sequence - worse than an honest N. Gap-fill after curation, sanity-check filled lengths against the gap estimate, and report which gaps were closed vs left.
• Hi-C-for-scaffolding vs Hi-C-for-phasing: the same library, two jobs. Scaffolding asks where on the chromosome (orders collapsed contigs); phasing asks which homolog (hifiasm --h1/--h2 during assembly). When handed "Hi-C, make chromosomes," the first question is haploid scaffolding or diploid phasing+scaffolding? - the tools and failure modes differ entirely.

Per-Method Failure Modes

Shipping the automated AGP as final

Trigger: publishing _scaffolds_final without curation. Mechanism: automated joins are inferences error-prone at junctions (~221 edits/Gb in VGP/DToL). Symptom: misjoins/inversions in the contact map; later-discovered wrong synteny/fusions. Fix: curate in PretextView/JBAT before any large-scale-order claim.

Conflating scaffold N50 with contig N50

Trigger: reporting only scaffold N50. Mechanism: scaffolding adds N-gaps, not sequence. Symptom: spectacular scaffold N50 over a small contig N50 - contiguity is nitrogen. Fix: report both N50s, gap count, total N bases separately.

Reference-scaffolding a structurally interesting genome

Trigger: RagTag on a non-model genome whose karyotype is studied. Mechanism: ordering to the reference imposes the reference's structure. Symptom: fusions/translocations/inversions silently erased; circular "discovery" of the reference karyotype. Fix: Hi-C + curation; use RagTag only as a hypothesis to test.

Scaffolding before breaking chimeras

Trigger: scaffolding contigs as given, contig-EC off. Mechanism: a chimeric contig drags region B into region A's chromosome; every join to it is wrong. Symptom: misjoins the contact map blames on the scaffolder. Fix: keep SALSA2 -m yes / YaHS contig-EC on; Tigmint for linked reads.

Treating Hi-C reads as a normal PE library

Trigger: bwa mem without -5SP, no dedup, or proper-pair logic. Mechanism: the two ends are different loci; mate rescue and insert-size filtering corrupt placement. Symptom: sparse/noisy contact map, weak joins. Fix: map each end separately (-5SP or per-end pipeline), dedup, MAPQ filter, enzyme-aware.

Gap-filling across a repeat

Trigger: running a gap-closer over the whole assembly to "finish" it. Mechanism: a long read bridges into a different copy of the repeat the gap sits in. Symptom: filled length far from the gap estimate; locally clean, globally mis-assembled. Fix: gap-fill after curation, sanity-check lengths, report closed-vs-left.

Quantitative Thresholds

Threshold	Source	Rationale
~221 curation interventions/Gb (67 breaks, 105 joins, 49 false-dup)	Howe 2021 GigaScience	expect the automated draft to be substantially editable, not finished
Hi-C ~50-100M valid pairs (vertebrate); rule-of-thumb ~1x coverage per ~1 Mb	VGP practice (~approx)	too little -> weak/missing joins, sparse noisy map; depends on genome size/repeats
Scaffold N50 / contig N50 > ~10x	curator reflex	contiguity is gap-borne; flag genome as contiguous-on-paper but unfinished
T2T chromosome = telomere at BOTH ends + zero internal gaps	T2T convention	tidk both-end recovery with internal Ns = chromosome-scale but not finished
RagTag default gap = 100 bp N	Alonge 2022	placeholder length is arbitrary; never a real distance estimate
MAPQ filter on Hi-C reads (e.g. YaHS -q 10)	mapping practice	drop repeat-ambiguous reads that create spurious joins

Common Errors

Error / symptom	Cause	Solution
_scaffolds_final looks chromosome-scale but synteny is wrong	shipped uncurated draft	curate the contact map in PretextView/JBAT
Huge scaffold N50, small contig N50	contiguity borne by N-gaps	report both; do not conflate
Reference-scaffolded genome "has" the reference's karyotype	RagTag imposed the structure	re-scaffold with Hi-C + curation
Sparse/noisy contact map, few joins	Hi-C mapped as normal PE / under-sequenced	remap with -5SP+dedup; add Hi-C coverage
YaHS makes spurious joins	enzyme/MAPQ misconfigured; chimeric contigs	set correct -e (omit for Omni-C), raise -q, keep contig-EC on
SALSA2 errors on input	: in FASTA headers or BED not name-sorted	rename headers; sort -k4 the BED
Filled gaps far from estimated length	gap-filler bridged wrong repeat copy	gap-fill post-curation; sanity-check lengths; report closed-vs-left

References

• Zhou C, McCarthy SA, Durbin R. 2023. YaHS: yet another Hi-C scaffolding tool. Bioinformatics 39:btac808.
• Ghurye J, et al. 2019. Integrating Hi-C links with assembly graphs for chromosome-scale assembly (SALSA2). PLoS Comput Biol 15:e1007273.
• Dudchenko O, et al. 2017. De novo assembly of the Aedes aegypti genome using Hi-C yields chromosome-length scaffolds (3D-DNA). Science 356:92-95.
• Durand NC, et al. 2016. Juicer provides a one-click system for analyzing loop-resolution Hi-C experiments. Cell Syst 3:95-98.
• Alonge M, et al. 2022. Automated assembly scaffolding using RagTag elevates a new tomato system for high-throughput genome editing. Genome Biol 23:258.
• Tang H, et al. 2015. ALLMAPS: robust scaffold ordering based on multiple maps. Genome Biol 16:3.
• Yeo S, et al. 2018. ARCS: scaffolding genome drafts with linked reads. Bioinformatics 34:725-731.
• Jackman SD, et al. 2018. Tigmint: correcting assembly errors using linked reads from large molecules. BMC Bioinformatics 19:393.
• Zhang H, et al. 2021. Fast alignment and preprocessing of chromatin profiles with chromap. Nat Commun 12:6566.
• Rhie A, et al. 2021. Towards complete and error-free genome assemblies of all vertebrate species (VGP). Nature 592:737-746.
• Howe K, et al. 2021. Significantly improving the quality of genome assemblies through curation. GigaScience 10:giaa153.
• Brown MR, Gonzalez de la Rosa PM, Blaxter M. 2025. tidk: a toolkit to rapidly identify telomeric repeats from genomic datasets. Bioinformatics 41:btaf049.
• Bionano Genomics. Bionano Solve Theory of Operation: Hybrid Scaffold (technical document) - hybrid scaffolding has no journal paper.

Related Skills

• long-read-assembly - Produces the contigs this skill orders into chromosomes
• hifi-assembly - hifiasm phases haplotypes (Hi-C --h1/--h2) before each is scaffolded
• assembly-polishing - Polish contigs before scaffolding; gaps remain N until gap-filling
• assembly-qc - Contig-vs-scaffold N50, BUSCO, and Merqury QV on the scaffolded result
• hi-c-analysis/hic-data-io - Hi-C read/pairs handling feeding the scaffolder
• comparative-genomics/synteny-analysis - Validate scaffold order/orientation against a related genome
• workflows/genome-assembly-pipeline - End-to-end QC -> assemble -> polish -> scaffold -> curate -> QC