Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL 60439, USA.
Curr Opin Biotechnol. 2012 Feb;23(1):72-6. doi: 10.1016/j.copbio.2011.12.017. Epub 2012 Jan 5.
Next-generation sequencing has changed metagenomics. However, sequencing DNA is no longer the bottleneck, rather, the bottleneck is computational analysis and also interpretation. Computational cost is the obvious issue, as is tool limitations, considering most of the tools we routinely use have been built for clonal genomics or are being adapted to microbial communities. The current trend in metagenomics analysis is toward reducing computational costs through improved algorithms and through analysis strategies. Data sharing and interoperability between tools are critical, since computation for metagenomic datasets is very high.
下一代测序技术改变了宏基因组学。然而,测序 DNA 不再是瓶颈,计算分析和解释才是瓶颈。计算成本是一个明显的问题,因为大多数我们常规使用的工具都是为克隆基因组学而构建的,或者正在被改编为微生物群落。宏基因组分析的当前趋势是通过改进算法和分析策略来降低计算成本。数据共享和工具之间的互操作性至关重要,因为宏基因组数据集的计算量非常大。