bio-comparative-genomics-whole-genome-alignment
Build whole-genome alignments using Progressive Cactus (Armstrong 2020 reference-free clade-level WGA), Minigraph-Cactus (Hickey 2024 pangenome-aware), LASTZ chain/net (UCSC pipeline), MUMmer4 (Marçais 2018 pairwise), minimap2 -x asm5/10/20 (Li 2018 fast pairwise), AnchorWave (Song 2022 WGD-aware), and Mauve / progressiveMauve (bacterial). Operates the HAL toolkit (Hickey 2013) for downstream extraction including halSynteny, halLiftover, halBranchMutations, and hal2maf. Use when constructing multi-species alignments for comparative-annotation projection (TOGA), synteny detection, conservation
npx skills add BioTender-max/awesome-bio-agent-skills --skill whole-genome-alignment --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
What it does
The skill orchestrates whole-genome alignments using a mix of tools including Progressive Cactus (reference-free), Minigraph-Cactus (pangenome-aware), LASTZ chain/net (reference-anchored), MUMmer4, minimap2, AnchorWave, and Mauve/progressiveMauve. It operates the HAL toolkit for downstream extraction such as halSynteny, halLiftover, halBranchMutations, and hal2maf. It is used when constructing multi-species alignments for comparative-annotation projection (TOGA), synteny detection, conservation analyses (phyloP / PhastCons), or pangenome graph construction; it also covers choosing between reference-free and reference-anchored approaches, tuning for closely vs distantly related genomes, and producing HAL files for downstream tools.
The workflow supports multiple CLI entry points:
cactus jobStore seqFile.txt output.hal --binariesMode localfor reference-free progressive WGAcactus-pangenome --reference ref name --vcffor pangenome graphslastz target.fa[multiple] query.fafollowed by the UCSC chain-net pipeline for pairwise reference-anchored alignmentminimap2 -ax asm5 ref.fa query.fa | samtools sortfor fast pairwise alignment of closely related genomesnucmer --maxmatch ref.fa query.fathendnadifffor MUMmer4 pairwise alignmentanchorwave proali --ploidy 4for WGD-aware sequence-level synteny alignment
How it works
The skill presents an algorithmic taxonomy and decision guidance among tools:
- Progressive Cactus aligns multiple genomes via a phylogenetic tree producing HAL multi-genome alignments (reference-free).
- Minigraph-Cactus builds a pangenome graph (VCF, GFA, BAM) by combining a minigraph SV graph with Cactus base-level alignments.
- LASTZ + UCSC chain/net yields a reference-anchored, pairwise alignment (chain, net, MAF).
- MUMmer4 (nucmer) provides fast pairwise alignments for closely related genomes.
- minimap2 (with -x asm5/asm10/asm20) offers fast pairwise alignment, with sensitivity varying by identity.
- AnchorWave provides WGD-aware sequence-level synteny alignment via CDS anchors and ploidy modeling.
- Progressive Mauve and others provide alternative multi-genome alignment options, especially for bacteria.
- HAL toolkit enables extraction and conversion (halSynteny, halLiftover, halBranchMutations, hal2maf) for downstream analyses.
The skill emphasizes choosing between reference-free and reference-anchored modes, scaling considerations (tree-guided vs pairwise), and producing HAL files for downstream tools.
When to use it
Use when constructing multi-species alignments for comparative annotation projection (TOGA), synteny detection, conservation analyses (phyloP / PhastCons), or pangenome graph construction. Use to select between reference-free (Cactus) and reference-anchored (LASTZ chains/nets) approaches and to tune sensitivity for closely vs distantly related genomes; to produce HAL files for downstream genome-wide tools.
What it can touch
- CLI tools:
cactus,cactus-pangenome,lastz,minimap2,nucmer,dnadiff,anchorwave. - HAL toolkit components:
halSynteny,halLiftover,halBranchMutations,hal2maf.
Caveats
- HAL file versions must be pinned to the version that produced them to avoid downstream tool incompatibilities.
- Cactus scaling depends on a proper guide tree; mis-specified trees lead to quadratic scaling and incorrect ancestral assemblies.
- Minimap2 may lose sensitivity at identity below ~70%; for distant comparisons prefer LASTZ.
- Repeats should be masked prior to certain pipelines (e.g., LASTZ) to avoid TE-induced spurious chains.
- Toil-based restarts require careful checkpointing; use
--restartwith the same jobStore path.
## Version Compatibility Reference examples tested with: Progressive Cactus 2.9.1+ (ComparativeGenomicsToolkit/cactus; Armstrong 2020 Nature 587:246), Minigraph-Cactus (Hickey 2024 Nat Biotech 42:663; bundled with Cactus 2.5+), HAL toolkit 2.3+ (Hickey 2013 Bioinformatics 29:1341), LASTZ 1.04.22+, UCSC kentUtils for chain/net (Kent 2003 PNAS 100:11484), MUMmer 4.0.0+, minimap2 2.28+, AnchorWave 1.2.5+, progressiveMauve 2.4.0+, sibeliaz 1.2.5+, winnowmap 2.03+ (Jain 2022 Nat Methods 19:705). Toil workflow runner 6.0+ for Cactus on HPC/cloud. Before using code patterns, verify installed versions match. If versions differ: - CLI: `cactus --help`, `cactus-pangenome --help`, `halStats --help`, `lastz --version`, `nucmer --version`, `minimap2 --version` - Python: `pip show toil`, `toil --version` If code throws `Toil workflow restart failure`, `HAL file corrupted`, `WDL workflow missing`, the Cactus pipeline is Toil-based and requires careful checkpointing; failed runs must be restarted with `--restart`. HAL file versions differ across hal-toolkit releases; pin the version that produced the file. # Whole Genome Alignment **"Align these multiple genomes at the base-pair level"** -> Choose
- Version Compatibility
- Algorithmic Taxonomy
- Decision Tree by Experimental Scenario
- Per-Tool Failure Modes
- Cactus running quadratically without species tree
- Branch-scale parameter mis-tuned
- Toil checkpoint restart failures
- Reference bias in LASTZ chain/net
- minimap2 sensitivity loss at < 70% identity
- Cactus producing wrong topology in ancestor assembly
- Repeats inflating LASTZ chain count
- HAL version mismatch breaking downstream tools
- Insufficient masking before Cactus
- AnchorWave WGD parameter mis-set
for fa in genomes/*.fa; do
BuildDatabase -name ${species}_DB $fa
RepeatModeler -database ${species}_DB -threads 16
RepeatMasker -lib ${species}_DB-families.fa -xsmall -pa 16 $fa
done
cat > seqFile.txt << 'EOF'
cactus jobStore_path seqFile.txt output.hal \
halStats output.hal
hal2maf output.hal reference_genome ucsc.maf --refGenome human --chunkSize 1000000
for chr in $(cut -f1 reference.fa.fai); doWhat does the bio-comparative-genomics-whole-genome-alignment skill do?
Build whole-genome alignments using Progressive Cactus (Armstrong 2020 reference-free clade-level WGA), Minigraph-Cactus (Hickey 2024 pangenome-aware), LASTZ chain/net (UCSC pipeline), MUMmer4 (Marçais 2018 pairwise), minimap2 -x asm5/10/20 (Li 2018 fast pairwise), AnchorWave (Song 2022 WGD-aware), and Mauve / progressiveMauve (bacterial). Operates the HAL toolkit (Hickey 2013) for downstream extraction including halSynteny, halLiftover, halBranchMutations, and hal2maf. Use when constructing multi-species alignments for comparative-annotation projection (TOGA), synteny detection, conservation
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill whole-genome-alignment --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.