Sequence analysis
Whole genome alignment
Compare genome assemblies with coordinate-aware alignment, dot plots, variant tables, and retained delta files.
Inputs
2 required
Methods
1 connected
- 01MUMmer4 · NUCmer Genome Alignment
MUMmer4 NUCmer aligns reference and query assemblies and returns coordinates, delta files, variants, statistics, and dot plots.
Use this templateWhat 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
- Best fit. Assembly comparison, synteny, rearrangements, polishing, and candidate differences
- Required input. Reference and query genome or contig FASTA files with assembly metadata
Benefits of whole genome alignment
- Clear correspondence. Scales to genome assemblies
- Connected evidence. Reports coordinate-aware differences
- Reusable output. Visualizes synteny and rearrangements
Primary limitations
- Method dependence. Assembly errors mimic variation
- Input dependence. Repeats create ambiguous matches
- Interpretive limit. Raw-read support is not included
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
Whole genome alignment is best suited to assembly comparison, synteny, rearrangements, polishing, and candidate differences. The result can support comparative review, sequence curation, annotation, profile construction, phylogenetic preparation, structural interpretation, or experimental planning when those downstream uses match the alignment scope.
Keep the alignment as evidence rather than a conclusion. Downstream claims should remain tied to sequence provenance, coverage, method agreement, relevant biological context, and any independent structural, evolutionary, or experimental support.
How to run whole genome alignment online
Use the connected workflow to keep input records, method settings, native outputs, warnings, and exports together. Review every stage before using the result for annotation, phylogeny, variant interpretation, or experimental decisions.
- Select assemblies. Choose a biologically appropriate reference and document assembly versions.
- Check quality. Review contiguity, contamination, haplotype status, and repeat content.
- Run NUCmer. Run MUMmer4 with explicit match mode, strand, and filtering settings.
- Review genome geometry. Inspect dot plots, coverage, coordinates, duplications, and rearrangements.
- Validate differences. Validate candidate variants or breakpoints with reads and orthogonal evidence.
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.
- Select assemblies. Choose a biologically appropriate reference and document assembly versions.
- Check quality. Review contiguity, contamination, haplotype status, and repeat content.
- Run NUCmer. Run MUMmer4 with explicit match mode, strand, and filtering settings.
- Review genome geometry. Inspect dot plots, coverage, coordinates, duplications, and rearrangements.
- 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.
FASTAPDBmmCIFReference and query genome or contig assemblies in FASTA format.
Outputs
- Alignment outputs.
FASTACSVTSVPDBJSONDelta and coordinate files, SNP and indel tables, alignment statistics, and dot plots.
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
Align genome assemblies and report coordinates and variants
MAFFT
Create configurable protein, DNA, or RNA alignments
Clustal Omega
Create scalable protein or nucleotide multiple-sequence alignments
StringZilla v5
Calculate pairwise global, local, or edit-distance score matrices
MMseqs2
Search and cluster large protein or nucleotide sequence sets
HMMER
Find homologs with profile hidden Markov models
MUSCLE5
Generate conventional or ensemble multiple-sequence alignments
FastTree
Estimate trees from large sequence alignments
IQ-TREE
Infer maximum-likelihood phylogenies from alignments
RAxML-NG
Run maximum-likelihood phylogenetic analysis
RNAalifold
Predict consensus RNA structure from an RNA alignment
USAlign
Align macromolecular structures and derive residue correspondence
Other sequence analysis workflows
Compare related approaches based on the molecular system, available evidence, required inputs, and decision you need to support.
Pairwise sequence alignment
Compares two biological sequences and reports their residue-to-residue correspondence or a defined pairwise score.
Multiple sequence alignment
Aligns three or more homologous sequences to identify shared positions, insertions, deletions, and conserved regions.
Global sequence alignment
Compares sequences end to end, including terminal differences and gaps across their full lengths.
Protein sequence alignment
Aligns amino-acid sequences using substitution-aware methods suited to protein evolution and function.
DNA sequence alignment
Aligns nucleotide sequences to compare homologous genes, amplicons, loci, transcripts, or constructs.
Local sequence alignment
Finds or scores the best-matching subsequences without forcing unrelated flanks into the comparison.
Structure-based sequence alignment
Uses three-dimensional correspondence to align residues whose sequence similarity alone may be weak.
Frequently asked questions
Reference and query genome or contig assemblies in FASTA format.
Delta and coordinate files, SNP and indel tables, alignment statistics, and dot plots.
Start from the scientific scope: global or local, pairwise or multiple, sequence or structure, and conventional or genome scale. Then record the method, substitution model, gap settings, sequence type, and any filtering rather than relying on defaults without provenance.
No. Scores and identities quantify similarity under a defined model. Homology is an evolutionary interpretation, and shared function requires additional evidence such as domain context, conserved residues, structure, phylogeny, experiments, or curated annotation.
Retain assembly accessions and versions, MUMmer4 settings, delta files, filters, coordinate conventions, and orthogonal validation.
A complete whole genome alignment project is usually quote-based because providers scope sequence curation, method selection, alignment review, interpretation, and downstream analysis together. Harvard’s FY26 bioinformatics core first defines deliverables and a time estimate, then charges $180–$265 per hour; MSU lists $84–$110 per hour and expects at least eight consultant hours for custom analysis.
The total depends on sequence count and length, input cleanup, molecular type, the number of methods compared, manual review, genome scale, figures, phylogenetic or structural follow-up, and whether the deliverable includes interpretation or only alignment files.
ProteinIQ self-service starts at $29 per month for academic Plus and $99 per month for commercial Pro, with the configured whole genome alignment run estimated in credits before submission. Done-for-you analysis is scoped separately and can include data preparation, method comparison, interpretation, and a reproducible handoff.
Start with a workflow you can inspect and edit
Add your inputs, review the settings, and keep every structure, score, table, and file connected to the step that produced it.