ArticlePLoS genetics2024
KmerAperture: Retaining k-mer synteny for alignment-free extraction of core and accessory differences between bacterial genomes.
Article in PLoS genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Metagenomics distilled: new k-mer-based methods.Nature reviews. Microbiology · 2025Article
- Reference-Free Variant Calling with Local Graph Construction with ska lo (SKA).Molecular biology and evolution · 2025Article
- Rapid, reference-free identification of bacterial pathogen transmission using optimized splitMicrobial genomics · 2025Article
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4 authors.
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Abstract
By decomposing genome sequences into k-mers, it is possible to estimate genome differences without alignment. Techniques such as k-mer minimisers, for example MinHash, have been developed and are often accurate approximations of distances based on full k-mer sets. These and other alignment-free methods avoid the large temporal and computational expense of alignment. However, these k-mer set comparisons are not entirely accurate within-species and can be completely inaccurate within-lineage. This is due, in part, to their inability to distinguish core polymorphism from accessory differences. Here we present a new approach, KmerAperture, which uses information on the k-mer relative genomic positions to determine the type of polymorphism causing differences in k-mer presence and absence between pairs of genomes. Single SNPs are expected to result in k unique contiguous k-mers per genome. On the other hand, contiguous series > k may be caused by accessory differences of length S-k+1; when the start and end of the sequence are contiguous with homologous sequence. Alternatively, they may be caused by multiple SNPs within k bp from each other and KmerAperture can determine whether that is the case. To demonstrate use cases KmerAperture was benchmarked using datasets including a very low diversity simulated population with accessory content independent from the number of SNPs, a simulated population where SNPs are spatially dense, a moderately diverse real cluster of genomes (Escherichia coli ST1193) with a large accessory genome and a low diversity real genome cluster (Salmonella Typhimurium ST34). We show that KmerAperture can accurately distinguish both core and accessory sequence diversity without alignment, outperforming other k-mer based tools.
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