Herath Damayanthi, Jayasundara Duleepa, Ackland David, Saeed Isaam, Tang Sen-Lin, Halgamuge Saman
Department of Mechanical Engineering, University of Melbourne, Parkville, 3010 Melbourne, Australia.
Department of Computer Engineering, University of Peradeniya, Prof. E. O. E. Pereira Mawatha, Peradeniya, 20400, Sri Lanka.
Comput Struct Biotechnol J. 2017 Sep 21;15:447-455. doi: 10.1016/j.csbj.2017.09.001. eCollection 2017.
Assessing biodiversity is an important step in the study of microbial ecology associated with a given environment. Multiple indices have been used to quantify species diversity, which is a key biodiversity measure. Measuring species diversity of viruses in different environments remains a challenge relative to measuring the diversity of other microbial communities. Metagenomics has played an important role in elucidating viral diversity by conducting metavirome studies; however, metavirome data are of high complexity requiring robust data preprocessing and analysis methods. In this review, existing bioinformatics methods for measuring species diversity using metavirome data are categorised broadly as either sequence similarity-dependent methods or sequence similarity-independent methods. The former includes a comparison of DNA fragments or assemblies generated in the experiment against reference databases for quantifying species diversity, whereas estimates from the latter are independent of the knowledge of existing sequence data. Current methods and tools are discussed in detail, including their applications and limitations. Drawbacks of the state-of-the-art method are demonstrated through results from a simulation. In addition, alternative approaches are proposed to overcome the challenges in estimating species diversity measures using metavirome data.
评估生物多样性是研究与特定环境相关的微生物生态学的重要一步。多种指数已被用于量化物种多样性，这是生物多样性的一项关键衡量指标。相对于测量其他微生物群落的多样性而言，测量不同环境中病毒的物种多样性仍然是一项挑战。宏基因组学通过开展宏病毒组研究在阐明病毒多样性方面发挥了重要作用；然而，宏病毒组数据具有高度复杂性，需要强大的数据预处理和分析方法。在这篇综述中，使用宏病毒组数据测量物种多样性的现有生物信息学方法大致分为序列相似性依赖方法和序列相似性独立方法。前者包括将实验中生成的DNA片段或组装体与参考数据库进行比较以量化物种多样性，而后者的估计则独立于现有序列数据的知识。本文详细讨论了当前的方法和工具，包括它们的应用和局限性。通过模拟结果展示了最先进方法的缺点。此外，还提出了替代方法以克服使用宏病毒组数据估计物种多样性指标时面临的挑战。
