1、theme_test()是将绘图修改成四周方框围起来的主题,挺常用的; 2、expand=c(0,0)参数是将x、y轴的两端留白区域去掉; 3、scale_fill_gradient()函数定义两个颜色的渐变色,前提是前面用了aes(fill=value),另外还有scale_fill_gradient2()和scale_fill_gradientn(),分别使用三种、多种颜色的渐变; 4、theme(...
theme(panel.grid.major.x=element_blank(),panel.grid.minor.x=element_blank())+#同时隐藏与x坐标轴相交的主次网格线 theme(panel.grid=element_blank())+ #隐藏网格线(等价于同时隐藏主次网格线) theme(panel.background=element_rect(fill='grey')) #面板背景色 Ⅳ.总体调整 theme(rect=element_rect())...
theme(panel.grid.major.x=element_blank(),panel.grid.minor.x=element_blank())+#同时隐藏与x坐标轴相交的主次网格线 theme(panel.grid=element_blank())+ #隐藏网格线(等价于同时隐藏主次网格线) theme(panel.background=element_rect(fill='grey')) #面板背景色 Ⅳ.总体调整 theme(rect=element_rect())...
theme( plot.margin = unit(c(1, 1, 1, 1), "cm"), panel.background = element_blank(), plot.title = element_text(size = 22, face = "bold", hjust = 0.5, margin = margin(b = 15)), axis.line = element_line(color = "black"), axis.title = element_text...
theme_niwot <- function(){ theme_test()+ theme(axis.text.y=element_text(color="black",size =8.5), axis.ticks= element_blank(), strip.background = element_blank(), strip.text = element_blank(), panel.spacing.y = unit(0,"cm"), plot.background = element_blank(), panel.border =...
p<- ggplot(data=go_enrich_df, aes(x=number, y=GeneNumber, fill=type)) +geom_bar(stat="identity", width=0.8) + coord_flip() +scale_fill_manual(values= CPCOLS) + theme_test() +scale_x_discrete(labels=labels) +xlab("GO term") +theme(axis.text=element_text(face ="bold", color...
", x="Area", title="Scatterplot", caption = "Source: midwest") plot(gg) #ggsave(filename = "test2.pdf", gg, width = 8, height = 5, dpi = 200) options(scipen=999) # turn-off scientific notation like 1e+48 library(ggplot2) theme_set(theme_bw()) # pre-set the bw theme....
今天小果想学习利用linkET包来绘制mantel test相关性热图 代码如下: 1. 安装需要的R包 install.packages(“ggplot2”)install.packages(“tidyverse”)install.packages(“ggrepel”) 2. 导入需要的R包 library(ggplot2)library(tidyverse)library(ggrepel)
mantel <- mantel_test(spec = spec,env = env) #spec参数后是物种组成数据,env参数后是环境因子数据 1. 2. 07 生成绘制连接弧线所需的数据框。包括连线的起点和终点坐标,根据mantel r的值确定线条粗细,mantel p的值确定线条颜色: n = nrow(corM) ...
#读取数据df<-read.csv("test.CSV",header =T)#创建一个向量,包含了图中将要展示的丰度最高的7个科top_phylum=c("Actinobacteria","Bacteroidetes","Firmicutes","Fusobacteria","Proteobacteria","Verrucomicrobia","[Thermi]")#将其他低丰度的...