1 计算相关系数和显著性

library(psych)
cor_matrix=corr.test(data1,data2,adjust="holm")
#相关系数
cmt <-cor_matrix$r
#显著性
pmt <- cor_matrix$p

2 构建显著性标记矩阵

if (!is.null(pmt)){
  ssmt <- pmt< 0.01
  pmt[ssmt] <-'**'
  smt <- pmt >0.01& pmt <0.05
  pmt[smt] <- '*'
  pmt[!ssmt&!smt]<- ''
} else {
  pmt <- F
}

3 可视化

3.1使用pheatmap包

library(pheatmap)
pheatmap(cmt,scale = "none", cluster_row = F, cluster_col = F, 
         border="black", fontsize_row=8, fontsize_col=8, display_numbers = pmt, fontsize_number = 10, 
         number_color = "black")

3.2 使用gplots包

#install.packages ("gplots")
library(gplots)
heatmap.2(cor_matrix$r,
          trace = 'none',
          notecol = 'black', srtCol = 0, 
          cellnote = pmt)
heatmap.2(cor_matrix$r, col=bluered, scale="column", trace = 'none')

3.3 使用corrplot包

library(corrplot)
coul=colorRampPalette(c("darkblue","white","darkred"))(10)
corrplot(cor_matrix$r,method ="circle",
         insig="label_sig",p.mat=cor_matrix$p,
         addgrid.col = "white",tl.col="black",
         tl.srt = 45,
         xpd = T,
         sig.level = c(0.01,0.05)
)