# Whole genome alignment Compare genome assemblies with coordinate-aware alignment, dot plots, variant tables, and retained delta files. [Open workflow](https://proteiniq.io/app/workflows/templates?template=whole-genome-alignment)[Contact sales](https://proteiniq.io/contact) ## More sequence alignment workflows ## Tools for whole genome alignment Use these methods to prepare inputs, run the core analysis, inspect outputs, and validate the evidence described in this workflow. [![MUMmer4](https://proteiniq.io/_next/image?url=%2Fimages%2Ftools%2Fmummer4.webp&w=96&q=75&dpl=dpl_J8tu6aF3F41kEvMFgYtuMXes1ynJ) ### MUMmer4 Align genome assemblies and report coordinates and variants](https://proteiniq.io/app/mummer4)[![MAFFT](https://proteiniq.io/_next/image?url=%2Fimages%2Ftools%2Fmafft.webp&w=96&q=75&dpl=dpl_J8tu6aF3F41kEvMFgYtuMXes1ynJ) ### MAFFT Create configurable protein, DNA, or RNA alignments](https://proteiniq.io/app/mafft)[![Clustal Omega](https://proteiniq.io/_next/image?url=%2Fimages%2Ftools%2Fclustal-omega.webp&w=96&q=75&dpl=dpl_J8tu6aF3F41kEvMFgYtuMXes1ynJ) ### Clustal Omega Create scalable protein or nucleotide multiple-sequence alignments](https://proteiniq.io/app/clustal-omega)[![StringZilla v5](https://proteiniq.io/_next/image?url=%2Fimages%2Ftools%2Fstringzilla.webp&w=96&q=75&dpl=dpl_J8tu6aF3F41kEvMFgYtuMXes1ynJ) ### StringZilla v5 Calculate pairwise global, local, or edit-distance score matrices](https://proteiniq.io/app/stringzilla)[![MMseqs2](https://proteiniq.io/_next/image?url=%2Fimages%2Ftools%2Fmmseqs2.webp&w=96&q=75&dpl=dpl_J8tu6aF3F41kEvMFgYtuMXes1ynJ) ### MMseqs2 Search and cluster large protein or nucleotide sequence sets](https://proteiniq.io/app/mmseqs2)[![HMMER](https://proteiniq.io/_next/image?url=%2Fimages%2Ftools%2Fhmmer.webp&w=96&q=75&dpl=dpl_J8tu6aF3F41kEvMFgYtuMXes1ynJ) ### HMMER Find homologs with profile hidden Markov models](https://proteiniq.io/app/hmmer)[![MUSCLE5](https://proteiniq.io/_next/image?url=%2Fimages%2Ftools%2Fmuscle5.webp&w=96&q=75&dpl=dpl_J8tu6aF3F41kEvMFgYtuMXes1ynJ) ### MUSCLE5 Generate conventional or ensemble multiple-sequence alignments](https://proteiniq.io/app/muscle5)[![FastTree](https://proteiniq.io/_next/image?url=%2Fimages%2Ftools%2Ffasttree.webp&w=96&q=75&dpl=dpl_J8tu6aF3F41kEvMFgYtuMXes1ynJ) ### FastTree Estimate trees from large sequence alignments](https://proteiniq.io/app/fasttree)[![IQ-TREE](https://proteiniq.io/_next/image?url=%2Fimages%2Ftools%2Fiq-tree.webp&w=96&q=75&dpl=dpl_J8tu6aF3F41kEvMFgYtuMXes1ynJ) ### IQ-TREE Infer maximum-likelihood phylogenies from alignments](https://proteiniq.io/app/iq-tree)[![RAxML-NG](https://proteiniq.io/_next/image?url=%2Fimages%2Ftools%2Fraxml-ng.webp&w=96&q=75&dpl=dpl_J8tu6aF3F41kEvMFgYtuMXes1ynJ) ### RAxML-NG Run maximum-likelihood phylogenetic analysis](https://proteiniq.io/app/raxml-ng)[![RNAalifold](https://proteiniq.io/_next/image?url=%2Fimages%2Ftools%2Fviennarna.webp&w=96&q=75&dpl=dpl_J8tu6aF3F41kEvMFgYtuMXes1ynJ) ### RNAalifold Predict consensus RNA structure from an RNA alignment](https://proteiniq.io/app/rnaalifold)[![USAlign](https://proteiniq.io/_next/image?url=%2Fimages%2Ftools%2Fusalign.webp&w=96&q=75&dpl=dpl_J8tu6aF3F41kEvMFgYtuMXes1ynJ) ### USAlign Align macromolecular structures and derive residue correspondence](https://proteiniq.io/app/usalign) ## What is whole genome alignment? Whole genome alignment is the process of arranging large genome assemblies or contig sets against one another to identify corresponding blocks and their coordinates. It can reveal collinearity, rearrangements, substitutions, insertions, and deletions. MUMmer4 NUCmer uses exact matches as anchors and extends them into alignments, producing assembly-to-assembly evidence rather than a substitute for raw-read mapping or independently validated variant calls. Use whole-genome alignment for comparing strains, assembly versions, haplotypes, related species, or a draft assembly against a reference. Reference choice, assembly quality, repeat content, ploidy, and evolutionary distance determine how coordinates and apparent rearrangements should be interpreted. Review dot plots and coordinate tables before focusing on variants. Duplications, inversions, translocations, unplaced contigs, and repeat-driven multi-mapping can create several valid correspondences. Preserve delta files, filters, reference names, and coordinate conventions so every reported difference can be traced back to the alignment. ### When to use whole genome alignment Use this approach when the comparison scope is clear: - Two assemblies need coordinate-level comparison. - A rearrangement or large insertion is suspected. - Candidate SNPs or indels need assembly-level context. ### Strengths and limitations Genome alignment retains long-range coordinates that a standard MSA cannot represent. NUCmer anchors and extends matches, producing alignments and dot plots that make collinearity or large structural differences visible. Repeats, collapsed copies and assembly errors can mimic biological rearrangements. Filter choices change which duplicated matches survive, while assembly direction and coordinate conventions affect every exported comparison. Candidate small variants still need read-level confirmation. ## Whole genome alignment methods NUCmer identifies maximal exact matches between nucleotide sequences and clusters consistent anchors before extension. Match-mode and filtering settings change sensitivity and the number of repeated correspondences retained. Dot plots summarize large-scale geometry, while coordinate and delta files preserve detailed alignments. SNP and indel reports should be interpreted only after repetitive and multiply aligned regions are understood. ## Whole genome alignment applications Comparing a new assembly with a reference can reveal inversions, duplications or missing segments for follow-up. A dot plot gives a rapid view of broad organization while coordinate and delta files preserve exact matched regions. For closely related genomes, the same alignment can nominate SNPs and indels. Those calls should be checked against repeats, read support and assembly quality before biological interpretation. ## How to run whole genome alignment online The workflow aligns a reference [FASTA](https://proteiniq.io/guides/how-to-make-a-fasta-file) and a query FASTA with MUMmer4 NUCmer and keeps native coordinate files and plots. 1. **Select assemblies.** Record reference and query versions, strand conventions and biological relationship. 2. **Check input quality.** Review contiguity, contamination, haplotype status and repeat content. 3. **Run genome alignment.** Use [MUMmer4](https://proteiniq.io/app/mummer4) NUCmer with recorded match and filtering settings. 4. **Inspect the dot plot.** Distinguish broad collinearity from inversions or off-diagonal blocks. 5. **Read detailed files.** Keep delta and coordinate outputs with the SNP or indel reports and their reference direction. 6. **Validate events.** Check important breakpoints or variants with raw-read evidence or an independent method. ## How to interpret whole genome alignment results A clean diagonal suggests broadly collinear assemblies; reverse diagonals indicate inversions, and off-diagonal blocks may represent translocations, duplications, or assembly placement differences. Confirm major events using assembly graphs, raw-read mappings, or an independent method. Coordinate conventions and reference direction must remain explicit in every exported table. ## How whole genome alignment works MUMmer4 NUCmer aligns reference and query assemblies and returns coordinates, delta files, variants, statistics, and dot plots. 1. **Select assemblies.** Choose a biologically appropriate reference and document assembly versions. 2. **Check quality.** Review contiguity, contamination, haplotype status, and repeat content. 3. **Run NUCmer.** Run MUMmer4 with explicit match mode, strand, and filtering settings. 4. **Review genome geometry.** Inspect dot plots, coverage, coordinates, duplications, and rearrangements. 5. **Validate differences.** Validate candidate variants or breakpoints with reads and orthogonal evidence. ## Inputs and outputs Check formats before running, then inspect and download the result from every workflow step. ### Inputs #### Alignment input `FASTA``PDB``mmCIF` Reference and query genome or contig assemblies in FASTA format. ### Outputs #### Alignment outputs `FASTA``CSV``TSV``PDB``JSON` Delta and coordinate files, SNP and indel tables, alignment statistics, and dot plots. ## Frequently asked questions AI answers from our docs. 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