R-ggplot 引用变量及批量作图+相关性
摘要:for (i in seq(5,62,2)) { value1 <- names(phe)[i] value2 <- names(phe)[i+1] phe %>% ggplot(aes(!!sym(value1),!!sym(value2)))+geom_point()+theme_bw()+st
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GO富集图
摘要:library(readxl) library('ggplot2') #pathway=read_xlsx('BSR_down.xlsx') pathway=read_xlsx('BSR-down.xlsx') dir() Class<-pathway$GO p = ggplot(pathway,a
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R语言画图-曼哈顿图-来源网络
摘要:#安装方法: # 设置安装源为清华大学TUNA镜像站点 options("repos" = c(CRAN="https://mirrors.tuna.tsinghua.edu.cn/CRAN/")) options(BioC_mirror="https://mirrors.tuna.tsinghua
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batch gene expression plot
摘要:library(tidyverse) library(ggpubr) #load data data = readxl::read_xlsx("gene_id.xlsx",sheet = 2) data1 = pivot_longer(data,cols = c(2,3,4,5,6,7),names
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相关性分析作图(热图+数值)/(直方图+数值)R语言
摘要:library('corrplot') library(xts) library(zoo) library(PerformanceAnalytics) setwd("F:/BaiduNetdiskWorkspace/") #读取数据 a<-readxl::read_xlsx("phe.xlsx",s
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