Varigraph: an accurate and widely applicable pangenome graph-based variant genotyper for diploid and polyploid genomes

Graph pangenome references can address single-reference bias, thereby enhancing the accuracy of variant genotyping and empowering downstream applications in population genetics and quan-titative genetics. However, existing pangenome-based genotyping methods struggle with large or complex pangenome graphs, particularly in polyploid genomes. Here, we introduce Varigraph, an algorithm that leverages the comparison of unique and repetitive k-mers between variant sites and short reads for genotyping both small and large variants. Varigraph outperforms current state-of-the-art linear and graph-based genotypers across non-human genomes while maintaining comparable accuracy in human genomes. By employing an efficient data structure, Varigraph achieves higher accuracy in repetitive regions while managing computational costs for large da-tasets. Notably, Varigraph is the first tool capable of effectively utilizing pangenome graphs for genotyping autopolyploids, enabling precise determination of allele dosage. This work provides a robust and accurate solution for genotyping non-human genomes and will facilitate genomic studies of polyploid crops.