Department of Mathematics and Statistics, University of Helsinki, Finland.
Department of Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Finland.
Bioinformatics. 2018 Jul 1;34(13):2308-2310. doi: 10.1093/bioinformatics/bty093.
The advent of genomic data from densely sampled bacterial populations has created a need for flexible simulators by which models and hypotheses can be efficiently investigated in the light of empirical observations. Bacmeta provides fast stochastic simulation of neutral evolution within a large collection of interconnected bacterial populations with completely adjustable connectivity network. Stochastic events of mutations, recombinations, insertions/deletions, migrations and micro-epidemics can be simulated in discrete non-overlapping generations with a Wright-Fisher model that operates on explicit sequence data of any desired genome length. Each model component, including locus, bacterial strain, population and ultimately the whole metapopulation, is efficiently simulated using C++ objects and detailed metadata from each level can be acquired. The software can be executed in a cluster environment using simple textual input files, enabling, e.g. large-scale simulations and likelihood-free inference.
Bacmeta is implemented with C++ for Linux, Mac and Windows. It is available at https://bitbucket.org/aleksisipola/bacmeta under the BSD 3-clause license.
Supplementary data are available at Bioinformatics online.
密集采样的细菌群体的基因组数据的出现,需要灵活的模拟器,以便根据经验观察来有效地研究模型和假设。Bacmeta 提供了在具有完全可调整连接网络的大型互联细菌群体中进行中性进化的快速随机模拟。突变、重组、插入/缺失、迁移和微观流行病等随机事件可以在离散的非重叠世代中使用 Wright-Fisher 模型进行模拟,该模型在任何所需基因组长度的显式序列数据上运行。使用 C++ 对象有效地模拟每个模型组件,包括基因座、细菌株、群体,最终是整个复合种群,并可以获取每个级别详细的元数据。该软件可以使用简单的文本输入文件在集群环境中执行,从而能够进行大规模模拟和无似然推断等操作。
Bacmeta 是用 C++ 为 Linux、Mac 和 Windows 编写的。它可在 BSD 3 条款许可证下在 https://bitbucket.org/aleksisipola/bacmeta 上获得。
补充数据可在 Bioinformatics 在线获得。