微生物多样性（扩增子/16S rDNA测序）—关联与进化分析方法
一、关联分析&进化关系内容及意义
a)RDA/CCA分析
基于对应分析发展而来的一种排序方法，又称多元直接梯度分析。RDA是基于线性模型，CCA是基于单峰模型。
意义：可以检测环境因子、样本、菌群三者之间的关系或者两两之间的关系。
b)OTU共表达网络分析
生态学中一般认为功能上关系密切的群落往往表现出丰度的“同升同降”，根据微生物群落丰度信息计算样本中物种之间的相关性，并据此划分不同的共变化组（CAG）。
意义：可发现物种间的相互关系、CAG与生理指标或环境因子间的关系。
c)系统进化发生树
推断能够揭示出有关生物进化过程的顺序，了解生物进化历史和机制，可以通过某一分类水平上序列间碱基的差异构建进化树。
二、关联分析&进化关系在论文中的描述
a)RDA/CCA分析
分析示意图
图片描述示例：
Redundancy analysis (RDA) of soil geochemical data and identification of significant Proteobacterial clades. Geochemical data were used to generate PCA and OTU abundance was used to generate the RDA. Factors and bacterial groups that had little influence on any of the sites (i.e. clustered near the center axis) or were similarly clustered were removed for clarity.
结果描述：
Principal Components Analysis revealed that much of the variance in soil properties and chemistry between the contaminated sites was associated with pH, arsenic, total chromium and Cr (VI) levels, while control soils were correlated with di and monovalent cations, bicarbonate, and phosphate concentrations.
Several novel proteobacterial groups MND1, LO133, and WJ2 were identified by redundancy analysis (RDA) to respond significantly to the contamination.
b)OTU共表达网络分析
分析示意图
图片描述示例：
Temporal dynamics in the gut microbiota of mice during the development of XX. OTU-level network diagram of XX key OTUs responding to the treatment of XX and XX. Node size indicates the mean abundance of each OTU. Lines between nodes represent correlations between the nodes they connect, with the colour saturation and line width indicating correlation magnitude: red represents positive correlation, grey represents negative correlation. Only lines corresponding to correlations with a magnitude greater than 0.5 are drawn. The OTUs are grouped into 11 CAGs by permutational multivariate analysis of variance (PERMANOVA) when P<0.005. The plots show the abundance of each CAG on Day -1, 2, 4 and 7 in 3 groups. Data in plots represent the total abundance of all OTUs in each CAG from each sample, which were then visualized by mean±s.e.m. Kruskal-Wallis test was used to analysis variation relative to the DSS group at the same time point. *P<0.05, **P<0.01, ***P<0.005.
结果描述：
To identify the potential interaction among OTUs responding to treatment with XX and XX, the XX key OTUs were clustered into 11 co-abundance groups (CAGs) based on SparCC correlation coefficients CAG7 and CAG8 were positively correlated to form one cluster, and CAG1 and CAG2 formed the other. These two main CAG clusters were negatively correlated with each other.
c)系统进化关系
分析示意图
图表描述示例：
Phylogenetic placement and distribution of nosZ OTUs in different dilution levels. The maximum likelihood phylogeny consists of representative nucleotide sequences for OTUs detected in all dilutions, as well as reference nosZ sequences obtained from genome sequencing projects. Symbols at different tips in the tree denote reference sequences, with color and shape indicating major taxonomic affiliation. Node confidence (n=500 bootstrap replicates) between 50–100% is shown (·), where symbol size is scaled to reflect support levels. The phylogeny is rooted at midpoint, and clades consisting only of reference sequences are collapsed. Barplots indicate the average relative abundance of each OTUs, averaged across replicates and normalized to the maximum average value detected within the respective dilutions. The number of shared and unique OTUs in each dilution treatment is shown as a Venn diagram within the tree, where circle size is proportional to the number of OTUs detected.
结果描述示例：
The phylogenetic tree based on the alignment of the obtained sequences together with nosZ sequences from known strains showed sequences clustering with nosZ from the α, β and γ-Proteobacteria. However, most sequences were distantly related to nosZ from the cultured organisms.
