scrm: efficiently simulating long sequences using the approximated coalescent with recombination.

scrm: efficiently simulating long sequences using the approximated coalescent with recombination.
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SCRM:使用重组的近似合并有效地模拟长序列。

DOI:
10.1093/bioinformatics/btu861
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发表时间:
2015-05-15
期刊:
Bioinformatics (Oxford, England)
影响因子:
--
通讯作者:
Lunter G
Lunter G
中科院分区:
其他
文献类型:
--
作者:
Staab PR;Zhu S;Metzler D;Lunter G

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动机:基于聚结的基因组序列模拟软件可以有效地通过计算机生成中短基因序列。然而,目前只能使用相当粗略的近似值来模拟下一代测序产生的基因组大小数据集。结果:我们提出了顺序合并重组模型(SCRM),这是一种有效、准确地近似重组合并的新方法,缩小了当前近似值与精确模型之间的差距。我们提出了一种有效的实现,并表明它可以模拟具有基本正确的链接结构的基因组规模数据集。可用性和实现:开源实现 scrm 可在 GPLv3 许可证的条件下在 https://scrm.github.io 上免费获得。联系方式:staab@bio.lmu.de 或 gerton.lunter@well.ox.ac.uk。补充信息:补充数据可在生物信息学在线获取。
Motivation: 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. Results: 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. Availability and implementation: The open source implementation scrm is freely available at https://scrm.github.io under the conditions of the GPLv3 license. Contact: staab@bio.lmu.de or gerton.lunter@well.ox.ac.uk. Supplementary information: Supplementary data are available at Bioinformatics online.
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