Staab Paul R, Zhu Sha, Metzler Dirk, Lunter Gerton
Department of Biology, Ludwig-Maximilians-Universität München, Planegg-Martinsried, Germany and Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK.
Bioinformatics. 2015 May 15;31(10):1680-2. doi: 10.1093/bioinformatics/btu861. Epub 2015 Jan 8.
Coalescent-based simulation software for genomic sequences allows the efficient in silico generation of short- and medium-sized genetic sequences. However, the simulation of genome-size datasets as produced by next-generation sequencing is currently only possible using fairly crude approximations.
We present the sequential coalescent with recombination model (SCRM), a new method that efficiently and accurately approximates the coalescent with recombination, closing the gap between current approximations and the exact model. We present an efficient implementation and show that it can simulate genomic-scale datasets with an essentially correct linkage structure.
用于基因组序列的基于合并的模拟软件能够在计算机上高效生成短、中规模的遗传序列。然而，目前要模拟下一代测序产生的基因组大小的数据集，只能使用相当粗略的近似方法。
我们提出了带重组的序列合并模型（SCRM），这是一种能高效且准确地近似带重组的合并过程的新方法，弥合了当前近似方法与精确模型之间的差距。我们给出了一个高效的实现，并表明它能够模拟具有基本正确连锁结构的基因组规模数据集。
