Toward Accurate and Quantitative Comparative Metagenomics.
Toward Accurate and Quantitative Comparative Metagenomics.
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DOI：
10.1016/j.cell.2016.08.007
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发表时间：
2016-08-25
期刊：
影响因子：
64.5
通讯作者：
Pollard KS
中科院分区：
文献类型：
--
作者：
Nayfach S;Pollard KS
鸟枪宏基因组学和计算分析用于比较微生物群落的分类和功能概况。利用这种方法来了解微生物在人类生物学和其他环境中的作用，需要定量数据总结，其值在样本和研究中具有可比性。目前，由于使用丰度统计数据，无法估计微生物群落的有意义参数，以及实验方案和数据清理方法带来的偏差，妨碍了可比性。应对这些挑战，沿着改进研究设计、数据访问、元数据标准化和分析工具，将使准确的比较宏基因组学成为可能。我们设想未来微生物组研究是可复制的，新的宏基因组可以轻松快速地与现有数据集成。只有这样，宏基因组学在预测性生态建模、强有力的关联研究和有效的微生物组医学方面的潜力才能得到充分实现。
Shotgun metagenomics and computational analysis are used to compare the taxonomic and functional profiles of microbial communities. Leveraging this approach to understand roles of microbes in human biology and other environments requires quantitative data summaries whose values are comparable across samples and studies. Comparability is currently hampered by the use of abundance statistics that do not estimate a meaningful parameter of the microbial community and biases introduced by experimental protocols and data-cleaning approaches. Addressing these challenges, along with improving study design, data access, metadata standardization, and analysis tools, will enable accurate comparative metagenomics. We envision a future in which microbiome studies are replicable and new metagenomes are easily and rapidly integrated with existing data. Only then can the potential of metagenomics for predictive ecological modeling, well-powered association studies, and effective microbiome medicine be fully realized.