corrplot example

# Returns a correlation coefficient, rounded, with any trailing zeros printed
  corr <- function(x, y, ...){
            as.numeric(formatC(round(cor(x = x, y = y, 
                                         use = "pairwise.complete.obs"), 2), 
                       format = "f", 2))
          } 

# Generate the matrix of correlation coefficients. In this example, I want to
# correlate a set of variables (A:F) with one other variable (G), rather than
# the more common matrix of A:G with A:G.
  library(dplyr)
  corr.matrix <- data %>%
                 group_by(group) %>%
                 summarise(A = corr(A, G),
                           B = corr(B, G),
                           C = corr(C, G),
                           D = corr(D, G),
                           E = corr(E, G),
                           F = corr(F, G))
  new.row.names <- corr.matrix[, 1]
  corr.matrix <- corr.matrix[, -1]
  rownames(corr.matrix) <- new.row.names
  corr.matrix <- as.matrix(corr.matrix)

# Generate the matrix of p-values for the correlation coefficients  
  p.matrix <- data %>%
              group_by(group) %>%
              summarise(A = cor.test(A, G)$p.value,
                        B = cor.test(B, G)$p.value,
                        C = cor.test(C, G)$p.value,
                        D = cor.test(D, G)$p.value,
                        E = cor.test(E, G)$p.value,
                        F = cor.test(F, G)$p.value)
 p.matrix <- p.matrix[, -1]
 rownames(p.matrix) <- new.row.names
 p.matrix <- as.matrix(p.matrix)

# Make the plot  
  library(corrplot)
  corrplot(corr.matrix, method = "color",
           addCoef.col = "black",
           tl.col = "black", tl.srt = 45,
           p.mat = p.matrix, sig.level = 0.2, insig = "blank")