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Local similarity analysis reveals unique associations among marine bacterioplankton species and environmental factors

机译:局部相似性分析揭示了海洋浮游物种与环境因素之间的独特关联

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Motivation: Characterizing the diversity of microbial communities and understanding the environmental factors that influence community diversity are central tenets of microbial ecology. The development and application of cultivation independent molecular tools has allowed for rapid surveying of microbial community composition at unprecedented resolutions and frequencies. There is a growing need to discern robust patterns and relationships within these datasets which provide insight into microbial ecology. Pearson correlation coefficient (PCC) analysis is commonly used for identifying the linear relationship between two species, or species and environmental factors. However, this approach may not be able to capture more complex interactions which occur in situ; thus, alternative analyses were explored.
机译:动机:表征微生物群落的多样性并了解影响群落多样性的环境因素是微生物生态学的中心宗旨。独立于耕种的分子工具的开发和应用允许以前所未有的分辨率和频率快速调查微生物群落组成。越来越需要识别这些数据集中的健壮模式和关系,以提供对微生物生态学的洞察力。皮尔逊相关系数(PCC)分析通常用于识别两个物种之间或物种与环境因素之间的线性关系。但是,这种方法可能无法捕获在现场发生的更复杂的交互。因此,探索了替代分析。

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