# layout = "fruchtermanreingold", path = Envnetplot,# 结果文件存储路径 fill = "Phylum", # 出图点填充颜色用什么值 size = "igraph.degree", # 出图点大小用什么数据 scale = TRUE, # 是否要进行相对丰度标准化 bio = TRUE, # 是否做二...
netpath = paste("./network3/",sep = "") dir.create(netpath) data(ps) ps gnum = 1 map = sample_data(ps) map$Group = "A" sample_data(ps) = map result = network.3(ps = ps, N = 500, big = TRUE, maxnode = 5, ...
#人工构造分组信息:将网络中全部OTU分为五个部分 netClu=data.frame(ID=row.names(otu_table),group=rep(1:5,length(row.names(otu_table)))[1:length(row.names(otu_table))] ) netClu$group = as.factor(netClu$group) #计算布局# result2 = PolygonClusterG (cor = cor,nodeGroup =netClu ) no...
gp = data.frame(ID = rownames(otu_table), group = sample(1:3, 100, replace = T)) layout = PolygonClusterG(cor = cor, nodeGroup = gp) # 生成网络图布局,'PolygonClusterG'是该论文中的布局 node = layout[[1]] # 提取节点 tax_table = ps_net %>% vegan_tax() %>% as.data.frame...
path = "./result_big_1000/" dir.create(path) result = network.2(ps = ps16s, N = 1000, big = TRUE, maxnode = 5, select_layout = TRUE, layout_net = "model_maptree2", r.threshold=0.4, p.threshold=0.01, label = FALSE, path = path, zipi = FALSE) # 多组网络绘制到一个面板...
pnet 基于聚类的”random”可视化 # layouts = c("circle","adj","circrand","eigen","random") #---计算网络布局-得到节点坐标=node#--- result2 = ranSNEClusterG (cor= cor,layout ="random") node = result2[[1]] library(dplyr)
(layout,"network",sep = "_"))+# geom_text_repel(aes(X1, X2,label=Phylum),size=4, data = plotcord)+# discard default grid + titles in ggplot2theme(panel.background=element_blank())+# theme(legend.position = "none") +theme(axis.title.x=element_blank(),axis.title.y=element_...
select_layout = FALSE, layout_net = "model_maptree2", r.threshold = 0.6, p.threshold = 0.05, maxnode = 2, method = "spearman", label = FALSE, lab = "elements", group = "Group", fill = "Phylum", size = "igraph.degree", ...
layout_net = "model_igraph", r.threshold=0.6, p.threshold=0.01, label = FALSE, path = path, zipi = FALSE) # 多组网络绘制到一个面板 p = result[[1]] # 全部样本网络参数比对 data = result[[2]] num= 3 # plotname1 = paste(path,"/network_all.jpg",sep = "") ...
head(netClu) 6 rows PolygonClusterG 根据分组,计算布局位置坐标 不同的模块按照分组聚集成不同的圆,并且圆形的大小一样。如果一个分组只有一个点,则这个点坐落在圆心位置。 Hide #---计算布局#--- result2=PolygonClusterG(cor =cor,nodeGroup =netClu ) node=result2[[1...