Max Planck Institute for Molecular Genetics, Berlin, Germany.
Department of Mathematics and Computer Science, Freie Universitat Berlin, Berlin, Germany.
PLoS Comput Biol. 2020 May 29;16(5):e1007843. doi: 10.1371/journal.pcbi.1007843. eCollection 2020 May.
Reconstructing haplotypes from sequencing data is one of the major challenges in genetics. Haplotypes play a crucial role in many analyses, including genome-wide association studies and population genetics. Haplotype reconstruction becomes more difficult for higher numbers of homologous chromosomes, as it is often the case for polyploid plants. This complexity is compounded further by higher heterozygosity, which denotes the frequent presence of variants between haplotypes. We have designed Ranbow, a new tool for haplotype reconstruction of polyploid genome from short read sequencing data. Ranbow integrates all types of small variants in bi- and multi-allelic sites to reconstruct haplotypes. To evaluate Ranbow and currently available competing methods on real data, we have created and released a real gold standard dataset from sweet potato sequencing data. Our evaluations on real and simulated data clearly show Ranbow's superior performance in terms of accuracy, haplotype length, memory usage, and running time. Specifically, Ranbow is one order of magnitude faster than the next best method. The efficiency and accuracy of Ranbow makes whole genome haplotype reconstruction of complex genome with higher ploidy feasible.
从测序数据中重建单倍型是遗传学中的主要挑战之一。单倍型在许多分析中起着至关重要的作用，包括全基因组关联研究和群体遗传学。对于同源染色体数量较高的情况，单倍型重建变得更加困难，因为这在多倍体植物中经常发生。这种复杂性进一步加剧了杂合性的增加，这意味着单倍型之间经常存在变体。我们设计了 Ranbow，这是一种用于从短读测序数据中重建多倍体基因组单倍型的新工具。Ranbow 整合了双等位基因和多等位基因位点中所有类型的小变体，以重建单倍型。为了在真实数据上评估 Ranbow 和当前可用的竞争方法，我们根据甘薯测序数据创建并发布了一个真实的黄金标准数据集。我们在真实和模拟数据上的评估清楚地表明，Ranbow 在准确性、单倍型长度、内存使用和运行时间方面的性能优越。具体来说，Ranbow 的速度比下一个最快的方法快一个数量级。Ranbow 的效率和准确性使得对具有更高倍性的复杂基因组进行全基因组单倍型重建成为可能。
