利用ggClusterNet绘制共线网络

今天小果学习一下ggClusterNet这个包，进行共线网络的绘制，代码如下：

1. 安装需要的R包

install.packages(“igraph”)

install.packages(“ggplot2”)

install.packages(“phyloseq”)

install.packages(“sna”)

install.packages(“devtools”)

install.packages(“tidyfst”)

devtools::install_github(“taowenmicro/ggClusterNet”)

install.packages(“tidyverse”)

1. 导入需要的R包

library(igraph)

library(phyloseq)

library(sna)

library(ggClusterNet)

library(ggplot2)

library(tidyfst)

library(tidyverse)

1. 代码展示

#导入示例数据#

data(ps)

#-提取丰度最高的指定数量的otu进行构建网络

#计算相关#

result = corMicro (ps = ps,

N = 150,

method.scale = “TMM”,

r.threshold=0.8,

p.threshold=0.05,

method = “spearman”

)

#提取相关矩阵

cor = result[[1]]

head(cor)

#网络中包含的OTU的phyloseq文件提取

ps_net = result[[3]]

#-导出otu表格

otu_table = ps_net %>%

vegan_otu() %>%

t() %>%

as.data.frame()

#人工构造分组信息：将网络中全部OTU分为五个部分

netClu=data.frame(ID=row.names(otu_table),group=rep(1:5,length(row.names(otu_table)))[1:length(row.names(otu_table))] )

netClu$group = as.factor(netClu$group)

#计算布局#

result2 = PolygonClusterG (cor = cor,nodeGroup =netClu )

node = result2[[1]]

#nodeadd 节点注释的：用otu表格和分组文件进行注释

#nodeadd函数只是提供了简单的用注释函数，用户可以自己在node的表格后面添加各种注释信息

tax_table = ps_net %>%

vegan_tax() %>%

as.data.frame()

#node节点注释#

nodes = nodeadd(plotcord =node,otu_table = otu_table,tax_table = tax_table)

#计算边#

edge = edgeBuild(cor = cor,node = node)

p <- ggplot() + geom_segment(aes(x = X1, y = Y1, xend = X2, yend = Y2,color = as.factor(cor)),

data = edge, size = 0.5) +

geom_point(aes(X1, X2,fill = Phylum,size = mean),pch = 21, data = nodes) +

scale_colour_brewer(palette = “Set1”) +

scale_x_continuous(breaks = NULL) + scale_y_continuous(breaks = NULL) +

theme(panel.background = element_blank()) +

theme(axis.title.x = element_blank(), axis.title.y = element_blank()) +

theme(legend.background = element_rect(colour = NA)) +

theme(panel.background = element_rect(fill = “white”, colour = NA)) +

theme(panel.grid.minor = element_blank(), panel.grid.major = element_blank())

ggsave(p,“ggcluster1.pdf”)

#分8组

netClu=data.frame(ID=row.names(cor),group=rep(1:8,length(row.names(cor)))[1:length(row.names(cor))] )

netClu$group = as.factor(netClu$group)

result2 = PolygonClusterG (cor = cor,nodeGroup =netClu )

node = result2[[1]]

# node节点注释#

nodes = nodeadd(plotcord =node,otu_table = otu_table,tax_table = tax_table)

#计算边#

edge = edgeBuild(cor = cor,node = node)

### 出图

p1 <- ggplot() + geom_segment(aes(x = X1, y = Y1, xend = X2, yend = Y2,color = as.factor(cor)),

data = edge, size = 0.5) +

geom_point(aes(X1, X2,fill = Phylum,size = mean),pch = 21, data = nodes) +

scale_colour_brewer(palette = “Set1″) +

scale_x_continuous(breaks = NULL) + scale_y_continuous(breaks = NULL) +

# labs( title = paste(layout,”network”,sep = “_”))+

# geom_text_repel(aes(X1, X2,label=Phylum),size=4, data = plotcord)+

# discard default grid + titles in ggplot2

theme(panel.background = element_blank()) +

# theme(legend.position = “none”) +

theme(axis.title.x = element_blank(), axis.title.y = element_blank()) +

theme(legend.background = element_rect(colour = NA)) +

theme(panel.background = element_rect(fill = “white”, colour = NA)) +

theme(panel.grid.minor = element_blank(), panel.grid.major = element_blank())

ggsave(“ggCluster.2.pdf”,p1)