GenomeScope 2.0 and Smudgeplot for reference-free profiling of polyploid genomes

An important assessment prior to genome assembly and related analyses is genome profiling, where the k-mer frequencies within raw sequencing reads are analyzed to estimate major genome characteristics such as size, heterozygosity, and repetitiveness. Here we introduce GenomeScope 2.0 (https://github.com/tbenavi1/genomescope2.0), which applies combinatorial theory to establish a detailed mathematical model of how k-mer frequencies are distributed in heterozygous and polyploid genomes. We describe and evaluate a practical implementation of the polyploid-aware mixture model that quickly and accurately infers genome properties across thousands of simulated and several real datasets spanning a broad range of complexity. We also present a method called Smudgeplot (https://github.com/KamilSJaron/smudgeplot) to visualize and estimate the ploidy and genome structure of a genome by analyzing heterozygous k-mer pairs. We successfully apply the approach to systems of known variable ploidy levels in the Meloidogyne genus and the extreme case of octoploid Fragariaxananassa. Prior to genome assembly, the raw sequencing reads must be analyzed for assessment of major genome characteristics such as genome size, heterozygosity, and repetitiveness. For this purpose, the authors introduce GenomeScope 2.0, an extension of GenomeScope for polyploid genomes, and Smudgeplot, which can estimate a genome's ploidy.