How to keep order of the correlation plot labels as same in the datafile?

Question

[WUSCHEL]

In Correlation plot, How can I keep the labels in the same order as in datafile, without rearranging?

This is the scripts I have been using;

library(corrplot) library(RColorBrewer) M <- cor(df) corrplot(M, method = "square", type = "upper", tl.col = "black", tl.cex= 0.4, order = "hclust", col = brewer.pal(n = 5, name = "RdYlBu"))

sample data

df <- structure(list(Cytosol_1 = c(2.8, 0.31, 1.21, 1.84, 0.93, 2.71, 2.03, 0.93, 0.89, 0.4, 0.32, 1.8, 1.16, 0.39, 1.16, 0.76, 1.17, 0.95, 0.58, 2.68, 0.88, 0.59, 1.49, 0.48, 0.51, 1.04, 0.89, 3.48, 1.47), Cytosol_2 = c(1.61, 0.22, 1.42, 1.97, 0.88, 1.46, 1.43, 0.74, 0.72, 0.43, 0.51, 2.07, 1.29, 0.71, 0.92, 0.57, 1.9, 0.84, 0.4, 2.72, 1.08, 0.96, 1.75, 0.24, 0.76, 0.99, 2.35, 2.06, 1.24 ), Cytosol_3 = c(1.76, 0.27, 0.77, 1.23, 0.93, 1.43, 0.7, 0.44, 0.58, 0.47, 0.57, 0.85, 0.79, 0.75, 0.95, 0.85, 1.49, 1.19, 0.72, 1.92, 1.11, 1.18, 1.03, 0.75, 0.58, 0.7, 0.79, 1.64, 1.14), Cytosol_4 = c(1.41, 0.98, 0.73, 2.31, 1.07, 1.1, 1.31, 0.66, 0.69, 0.51, 0.53, 1.3, 1.37, 1.55, 0.99, 1.27, 1.22, 0.89, 1.21, 1.56, 1.14, 0.7, 0.3, 0.63, 1.73, 1.49, 0.92, 1.8, 1.7), Cytosol_5 = c(2.36, 0.25, 1.43, 2.76, 0.91, 2.88, 2.73, 0.79, 0.71, 0.15, 0.92, 1.94, 1.12, 0.64, 2.07, 0.68, 1.51, 0.66, 0.51, 1.91, 1.61, 0.68, 0.73, 0.7, 0.94, 1.24, 2.45, 3.12, 1.58), Ribosome_6 = c(1.52, 1.09, 1.58, 1.29, 0.92, 1.12, 0.8, 0.51, 0.87, 0.58, 0.42, 0.72, 1.39, 1.14, 1.87, 1.11, 1.11, 1.07, 0.84, 1.11, 1.17, 0.45, 0.49, 0.59, 0.89, 0.79, 0.67, 1.66, 1.86), Ribosome_7 = c(4.16, 0.98, 1.79, 2.21, 1.21, 1.31, 1.01, 0.02, 0.82, 0.51, 0.81, 0.73, 2.34, 1.04, 1.99, 0.92, 2.2, 0.74, 0.25, 1.71, 1.43, 0.67, 1.19, 0.49, 1.5, 1.14, 0.92, 3.67, 2.68), Ribosome_8 = c(2.02, 0.95, 1.79, 1.47, 0.87, 1.88, 0.97, 0.51, 0.77, 0.66, 0.54, 1, 1.54, 0.92, 1.73, 1.32, 1.89, 0.97, 0.87, 1.26, 1.1, 0.61, 0.49, 0.57, 0.91, 0.76, 0.86, 3.37, 3.1), Ribosome_9 = c(2.67, 0.45, 1.45, 1.41, 0.56, 1.93, 1.29, 0.44, 0.58, 0.38, 0.3, 1.15, 1.5, 0.67, 1.38, 0.72, 1.71, 0.74, 0.5, 2.2, 1.36, 0.74, 1.06, 0.54, 0.72, 0.83, 1.27, 2.55, 1.4), Ribosome_10 = c(2.19, 0.55, 1.39, 1.56, 0.62, 1.67, 1.31, 0.47, 0.46, 0.35, 0.4, 1.02, 1.32, 0.7, 0.96, 0.6, 1.63, 0.94, 0.38, 1.6, 0.92, 0.71, 0.81, 0.56, 0.77, 0.73, 1.14, 2.42, 1.11 ), ER_17 = c(1.41, 0.29, 0.32, 0.76, 0.7, 2.75, 2.78, 0.8, 0.96, 0.28, 0.82, 2.15, 1.19, 0.55, 0.78, 0.97, 1.42, 1.22, 0.92, 1.84, 0.6, 0.69, 0.43, 0.39, 0.38, 0.48, 0.36, 2.17, 1.03), ER_18 = c(1.02, 0.43, 0.98, 1.91, 0.88, 3.19, 1.05, 1.65, 0.53, 1.08, 0.39, 1.1, 0.36, 0.56, 0.58, 1.13, 1.25, 1.03, 0.79, 1.67, 0.56, 0.84, 1.17, 1.05, 0.18, 0.69, 0.09, 1.58, 0.47), ER_19 = c(0.58, 0.72, 0.58, 1.42, 0.52, 2.18, 0.95, 0.32, 1.44, 0.86, 0.24, 0.8, 0.62, 0.34, 0, 1.29, 1.29, 0.84, 1.43, 4.48, 1.82, 0.97, 0.83, 1.25, 0.29, 0.03, 1.48, 1.72, 1.89), Extracellular_20 = c(2.77, 0.43, 2.23, 1.86, 0.51, 2.96, 1.41, 0.91, 0.61, 0.64, 0.84, 2.03, 1.34, 0.69, 0.82, 0.5, 1.18, 0.77, 0.59, 1.65, 1, 0.74, 1, 0.55, 1.38, 1.38, 1.82, 1.58, 1.02), Extracellular_21 = c(3.4, 0.67, 1.91, 1.76, 0.77, 1.65, 1.04, 0.48, 0.53, 0.34, 0.48, 1.24, 1.49, 1.07, 1.24, 0.81, 1.4, 0.85, 0.46, 1.52, 0.9, 0.81, 0.6, 0.57, 1.32, 1.3, 2.22, 1.29, 0.98), Extracellular_22 = c(0.52, 0.01, 0.33, 2.25, 1.05, 2.63, 2.5, 0.99, 0.53, 1.21, 1.43, 3.2, 0.32, 0.2, 0.23, 0.52, 1.07, 0.51, 0.55, 2.58, 1.5, 1.19, 2.16, 0.81, 0.02, 0.1, 0.2, 2.38, 1.36), Extracellular_23 = c(0.16, 0, 0, 1.8, 0.74, 1.45, 2.6, 0.8, 1.68, 1.63, 2.41, 1.46, 0.52, 0.67, 0.05, 1.12, 0.78, 0.62, 0.56, 1.74, 1.03, 1.74, 1.14, 1.33, 0, 0, 0, 0.96, 1.46)), class = "data.frame", row.names = c(NA, -29L))

Also, want to change the color code; Red for +1 and bluue for -1? How can I do this ?

[cpad0112]

The line was changed to m <- cor(df) instead of correlation_matrix <- cor(df). try this to get the same image as OP posted:

corrplot(
m,
title="Lorem lipsum",
method = "circle",
type = "upper",
tl.col = "black",
col = colorRampPalette(c("blue", "red"))(5),
tl.cex = 1.2,
cl.cex=1.2,
mar = c(2, 0, 2, 0)
)

[WUSCHEL]

Thank you cpad0112. You do not know how I am grateful for your kind helps. Thank you very much!!!!

[cpad0112]

However, i guess you are better off using following code:

>corrplot(m, method = "square", type = "upper",tl.col = "black", tl.cex= 1.4,cl.cex= 1.4, col =colorRampPalette(c("blue","red"))(5), order = "hclust", hclust.method = "ward.D2")

add some statistical significance and plot:

p.mat <- cor.mtest(df)

corrplot(
    m,
    title = "Dummy name here",
    method = "circle",
    type = "upper",
    tl.col = "black",
    col = colorRampPalette(c("blue", "red"))(5),
    order = "hclust",
    hclust.method = "ward.D2",
    tl.cex = 1.2,
    cl.cex=1.2,
    outline = T,
    mar=c(0,0,4,5),
    sig.level = 0.05,
    p.mat = p.mat$p
)

Take commets/suggestions from other members on better/best correlation methods.