Australian Centre for Ecogenomics, School of Chemistry and Molecular Biosciences, The University of Queensland, St Lucia, QLD 4072, Australia.
Nucleic Acids Res. 2012 Jul;40(12):e94. doi: 10.1093/nar/gks251. Epub 2012 Mar 19.
We introduce Grinder (http://sourceforge.net/projects/biogrinder/), an open-source bioinformatic tool to simulate amplicon and shotgun (genomic, metagenomic, transcriptomic and metatranscriptomic) datasets from reference sequences. This is the first tool to simulate amplicon datasets (e.g. 16S rRNA) widely used by microbial ecologists. Grinder can create sequence libraries with a specific community structure, α and β diversities and experimental biases (e.g. chimeras, gene copy number variation) for commonly used sequencing platforms. This versatility allows the creation of simple to complex read datasets necessary for hypothesis testing when developing bioinformatic software, benchmarking existing tools or designing sequence-based experiments. Grinder is particularly useful for simulating clinical or environmental microbial communities and complements the use of in vitro mock communities.
我们介绍 Grinder(http://sourceforge.net/projects/biogrinder/),这是一个开源的生物信息学工具,可用于模拟参考序列的扩增子和鸟枪法(基因组、宏基因组、转录组和元转录组)数据集。这是第一个用于模拟扩增子数据集(例如 16S rRNA)的工具,这些数据集被微生物生态学家广泛使用。Grinder 可以为常用的测序平台创建具有特定群落结构、α 和 β 多样性以及实验偏差(例如嵌合体、基因拷贝数变异)的序列文库。这种多功能性允许创建用于开发生物信息学软件、基准测试现有工具或设计基于序列的实验时进行假设检验的简单到复杂的读取数据集。Grinder 特别适用于模拟临床或环境微生物群落,并补充了体外模拟群落的使用。