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Panmap: Scalable phylogeny-guided alignment, genotyping, and placement on pangenomes.
Alexander M Kramer1,2, Alan Zhang1,2, Nicolas Ayala1,2,3
1Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, USA.
Biorxiv : the Preprint Server for Biology
|April 10, 2026
Summary
Panmap efficiently analyzes large-scale pangenomes by leveraging evolutionary structure. This tool enables rapid read mapping and phylogenetic analysis, overcoming computational challenges in population genomics.
Area of Science:
- Genomics
- Bioinformatics
- Computational Biology
Background:
- Pangenomes offer comprehensive population-level genetic variation data.
- Scalable computational methods are needed for large pangenome analysis.
Purpose of the Study:
- To develop a computationally efficient tool, Panmap, for analyzing large-scale pangenomes.
- To enable read mapping, alignment, and genotyping against mutation-annotated pangenomes.
Main Methods:
- Development of Panmap, a tool utilizing phylogenetically compressed k-mer indexes.
- Storing sequence differences along evolutionary branches to reduce index size and construction time.
- Applying Panmap for read placement, haplotype identification, and ancient DNA analysis.
Main Results:
- Panmap significantly reduces index size (up to 600-fold) and construction time (over three orders of magnitude).
- Achieved rapid read placement against millions of genomes (e.g., 8 million in under two minutes).
- Demonstrated accurate haplotype identification and sensitive ancient DNA placement.
Conclusions:
- Panmap makes large-scale pangenomes computationally tractable for various analyses.
- The tool facilitates read mapping, genome assembly, phylogenetic placement, and metagenomic analysis.
- Panmap advances population genomics and evolutionary studies by enabling efficient pangenome utilization.
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