三分钟学会如何绘制聚类+基因表达趋势+功能注释组合图

三分钟学会如何绘制聚类+基因表达趋势+功能注释组合图

今天小果想安利一个R包ClusterGVis，分享一下如何利用ClusterGVis包绘制聚类+基因表达趋势+功能注释组合图，下面进行操作，代码如下：

1. 安装需要的R包

install.packages(“devtools”)

devtools::install_github(“junjunlab/ClusterGVis”)

install.packages(“Biobase”)

1. 载入需要的R包

library(ClusterGVis)

library(Biobase)

1. 代码展示

#数据读取-基因表达矩阵文件

expr <- read.table(“exp.txt”,header = T,row.names = 1,sep = “\t”)

#开始绘图

ck <- clusterData(exp = expr,

cluster.method = “kmeans”,

cluster.num = 8)

#需要标记的基因名称

markGenes = rownames(expr)[sample(1:nrow(expr),30,replace = F)]

pdf(‘clustergene.pdf’,height = 10,width = 6,onefile = F)

visCluster(object = ck,

plot.type = “heatmap”,

column_names_rot = 45,

markGenes = markGenes)

dev.off()

library(org.Mm.eg.db)

# enrich for clusters

enrich <- enrichCluster(object = ck,

OrgDb = org.Mm.eg.db,

type = “BP”,

pvalueCutoff = 0.05,

topn = 5,

seed = 5201314)

pdf(‘enrich.pdf’,height = 10,width = 11,onefile = F)

visCluster(object = ck,

plot.type = “both”,

column_names_rot = 45,

show_row_dend = F,

markGenes = markGenes,

markGenes.side = “left”,

genes.gp = c(‘italic’,fontsize = 12,col = “black”),

annoTerm.data = enrich,

line.side = “left”,

go.col = rep(ggsci::pal_d3()(8),each = 5),

go.size = “pval”,

mulGroup = c(2,2,2),

mline.col = c(ggsci::pal_lancet()(3)))

dev.off()

看起来绘图效果非常不错yyds，用起来非常方便，今天小果的分享就到这里，有需要的可以借鉴学习,下期再见。