PanKmer:k-mer based and reference-free pangenome analysis

Abstract

AbstractSummaryPangenomes are replacing single reference genomes as the definitive representation of DNA sequence within a species or clade. Pangenome analysis predominantly leverages graph-based methods that require computationally intensive multiple genome alignments, do not scale to highly complex eukaryotic genomes, limit their scope to identifying structural variants (SVs), or incur bias by relying on a reference genome. Here, we present PanKmer, a toolkit designed for reference-free analysis of pangenome datasets consisting of dozens to thou-sands of individual genomes. PanKmer decomposes a set of input genomes into a table of observedk-mers and their presence-absence values in each genome. These are stored in an efficientk-mer index data format that encodes SNPs, INDELs, and SVs. It also includes functions for downstream analysis of thek-mer index, such as calculating sequence similarity statistics between individuals at whole-genome or local scales. For example,k-mers can be “anchored” in any individual genome to quantify sequence variability or conservation at a specific locus. This facilitates workflows with various biological applications, e.g. identifying cases of hybridization between plant species. PanKmer provides researchers with a valuable and convenient means to explore the full scope of genetic variation in a population, without reference bias.Availability and implementationPanKmer is implemented as a Python package with components written in Rust, released under a BSD license. The source code is available from the Python Package Index (PyPI) athttps://pypi.org/project/pankmer/as well as Gitlab athttps://gitlab.com/salk-tm/pankmer. Full documentation is available athttps://salk-tm.gitlab.io/pankmer/.Supplementary informationSupplementary data are available online