How to improve visibility of correlation plot in R?
I am trying to create a correlation plot in R, but the output looks blurry or unclear, and I can't view the details properly. Below are the steps I followed:
library(corrplot)
library(Hmisc)
col = colorRampPalette(c("navy", "white", "red"))(20)
c_df = Hmisc::rcorr(cor(df), type='spearman')
M = c_df$r[1:3, 4:80]
p.mat = c_df$P[1:3, 4:80]
corrplot(M, method="color", col=col, addCoef.col = "black", tl.col="black",
p.mat = p.mat, sig.level = 0.05, insig = "blank", diag=FALSE )
but the results are not really visible. I used png() function also to assign width and height but it gave me same results.
The input is:
df = structure(list(hsa.miR.101.3p = c(11.6, 11.8, 11.5, 11.2, 11.5,
11.7, 11.8, 11.4, 10.9, 10.9, 11.3, 11.3, 11.4, 11.1, 11.4, 11.4,
11.8, 11.3, 11.6, 11.7, 12.7), hsa.miR.23a.3p = c(13.9, 13.6,
14, 13.3, 13.9, 13.8, 13.7, 14, 13.4, 13.4, 14.1, 13.6, 14, 13.5,
13.8, 13.5, 14.2, 14, 14.3, 14.4, 13.4), hsa.miR.424.5p = c(14.4,
13.9, 14, 14.3, 14.1, 13.6, 13.8, 14.3, 13.8, 13.8, 14.2, 14.5,
14.2, 14.1, 14.5, 15.3, 14.5, 14.4, 14.5, 14.2, 15.3), CFTR = c(6,
7.2, 6, 5.9, 6, 5.9, 6.4, 6.5, 7.2, 6.2, 5.9, 5.5, 6.1, 8, 6.6,
5.6, 6.5, 5.9, 6.4, 6.7, 5.9), ITGA3 = c(11.9, 11.8, 12, 11.7,
12.1, 11.8, 11.9, 11.8, 11.9, 12.2, 11.5, 11.7, 11.9, 11.8, 12.1,
11.7, 12.1, 12, 12.2, 12.2, 12), ST7L = c(8.1, 8.1, 8.3, 8.2,
8.2, 8.2, 8.2, 8.2, 8.1, 7.9, 8.2, 8.4, 8.6, 8.2, 8.6, 8.3, 8.2,
8.4, 8.5, 8.4, 8.2), ANLN = c(9, 8, 8.9, 8.8, 8.9, 8.4, 9.7,
9.3, 10.1, 9.2, 9.1, 9.7, 9.1, 9.4, 9.1, 8, 9.3, 9.1, 8.8, 9,
8.6), FAS = c(8.9, 7.8, 8, 8.3, 8.1, 8.7, 8, 8.8, 8, 8.6, 8.2,
9, 9.1, 8.3, 8.3, 8.2, 8.2, 8.7, 8, 8.2, 7.9), CDH1 = c(12.5,
12.7, 12.6, 12.4, 12.5, 12.4, 12.8, 12.8, 13, 12.9, 12.5, 12.7,
12.9, 12.6, 12.5, 12.7, 12.9, 12.8, 12.1, 12.6, 12.3), PIK3CB = c(10.8,
10.6, 10.9, 10.6, 10.9, 10.5, 10.4, 10.5, 10.5, 10.6, 10.2, 10.6,
10.5, 10.7, 11.2, 10.4, 10.9, 11, 10.9, 11, 10.2), PRDM1 = c(7.1,
7, 6.4, 7, 7.2, 6.8, 7.1, 6.9, 6.7, 7.7, 6.3, 7.1, 7.4, 6.9,
7.3, 7, 8.3, 6.7, 7, 7.1, 6.7), SPI1 = c(9.5, 9.6, 9.6, 10, 8.8,
9.6, 9.5, 9.5, 9.3, 9.1, 9.7, 9.7, 9.4, 9.3, 9.3, 9.8, 9.4, 9.4,
9.2, 8.8, 9.4), KLF6 = c(11.8, 11.7, 11.4, 11.7, 11.4, 11.5,
11.7, 11.1, 11.5, 11.7, 11.6, 12.2, 11.8, 11.6, 11.4, 11.8, 12,
11.8, 11.7, 11.3, 11.6), RHOA = c(12.4, 12.2, 12.4, 12.5, 12.2,
12.3, 12.3, 12.4, 12.8, 12.3, 12.4, 12.4, 12.3, 12.3, 12.4, 12.3,
12.3, 12.3, 12.3, 12.3, 12.5), TGFBR3 = c(13, 13.3, 13.4, 12.9,
13.2, 12.9, 12.5, 12.4, 11.8, 12.5, 12.2, 12.5, 12.8, 12.8, 13,
12.9, 12.8, 13, 13.6, 13, 12.2), PTGS2 = c(8.5, 7.2, 8.3, 8.5,
8.9, 8.7, 7.4, 7.5, 6.2, 6.3, 8.8, 10.6, 6.6, 7.3, 6.7, 9.3,
7.1, 7.5, 8.7, 6.6, 6.7), EED = c(8.9, 8.9, 8.8, 8.8, 8.8, 8.6,
8.8, 8.8, 9.3, 8.8, 9, 9, 8.9, 9, 8.8, 8.8, 8.7, 8.9, 8.8, 8.9,
8.4), FGFR1 = c(11.3, 11.8, 11.3, 11.9, 11.6, 11.9, 11.7, 11.7,
11.7, 11.5, 11.8, 11.9, 11.8, 11.7, 11.5, 12, 12.3, 11.5, 11.2,
11.4, 11.9), CDC14A = c(8.4, 8.5, 8.3, 8.1, 8.3, 8.1, 8.2, 8.5,
8.2, 8.2, 8, 8.3, 8.1, 8.1, 8.4, 8.2, 8.4, 8.1, 8.4, 8.6, 8.1
), HSP90AA1 = c(13.9, 14, 13.5, 13.4, 14, 13.8, 13.5, 13.4, 13.7,
13.9, 13.5, 13.5, 13.7, 14, 14.2, 13.3, 14, 13.7, 13.7, 14, 13.5
), MEF2C = c(10, 9.9, 10.3, 10.5, 9.8, 10.5, 10.5, 10.5, 10.2,
10.2, 10.3, 10.3, 10.5, 10.2, 10.2, 10.6, 10.3, 9.9, 9.8, 10.2,
9.8), NLK = c(9, 8.8, 9.1, 9, 8.8, 9, 9, 9, 8.9, 9, 9.1, 8.9,
9, 8.9, 8.9, 9, 9.1, 8.9, 9.2, 9.1, 8.6), JAK2 = c(9.7, 9.3,
10, 9.2, 9.3, 9.8, 9.5, 9.4, 8.5, 9, 10.1, 9.6, 9.5, 9.1, 9.3,
9.7, 9.1, 9.8, 10.1, 9.3, 9), HIF1A = c(10.8, 10.8, 10.9, 11.2,
10.8, 10.9, 11, 10.9, 10.6, 11.5, 10.9, 10.9, 11.3, 10.8, 11.1,
11, 11, 10.8, 10.8, 10.8, 10.4), SMAD7 = c(10.3, 10.9, 10.8,
10.4, 10.7, 10.3, 10.2, 10.4, 10.1, 10.3, 10.2, 9.9, 10.4, 10.1,
10.4, 10.3, 10.3, 10.4, 10.9, 10.4, 10.7), XIAP = c(9.7, 9.8,
9.9, 9.8, 9.9, 9.7, 9.6, 9.7, 9.4, 9.8, 9.7, 9.4, 9.8, 9.7, 9.9,
9.7, 9.8, 9.5, 9.9, 9.9, 9.7), FMR1 = c(11, 11.4, 11.1, 10.6,
11.6, 11, 10.9, 11, 10.3, 10.9, 10.2, 10.4, 11.1, 10.9, 11.2,
10.7, 11.1, 11.3, 11.5, 11.5, 11), EYA1 = c(5.5, 5.1, 5.4, 5.4,
5.7, 5.3, 5.5, 5.3, 5.3, 5.4, 5.4, 5.9, 5.3, 5.4, 5.3, 5.2, 5.3,
5.6, 5.5, 5, 5.3), CCNE1 = c(9.7, 9.1, 9.3, 9.6, 10.4, 9.5, 10.3,
9.8, 10.6, 10, 9.6, 10.2, 10.4, 10.1, 10, 9.7, 10.2, 9.7, 9.2,
9.7, 9.8), CDK6 = c(10.7, 10.9, 10.6, 11, 10.5, 10.7, 11.1, 11.1,
10.9, 11, 11.1, 10.8, 10.9, 11, 10.8, 11.2, 10.7, 10.7, 10.3,
10.9, 10.7), MET = c(11.5, 11.5, 11.5, 11.3, 11.1, 11.1, 11.6,
11.7, 11.4, 11.3, 11.6, 11.8, 11.4, 11.3, 11.2, 11.9, 11.5, 11.6,
11.3, 11.5, 11), EZH2 = c(8.7, 8.3, 8.7, 8.7, 8.9, 8.5, 9.2,
8.8, 9.4, 8.6, 8.6, 9.4, 8.7, 8.7, 8.4, 8.3, 8.7, 8.8, 8.6, 8.5,
8.5), CXCL12 = c(7.6, 7.1, 7.1, 8.2, 6.8, 6.5, 7.4, 7.6, 7.9,
6.5, 8, 6.5, 7.3, 7.1, 6.4, 8.1, 8, 7.4, 6.4, 7.8, 8), CUL2 = c(10.3,
10.1, 10.3, 10, 10.6, 10.1, 9.9, 10, 10, 9.9, 9.7, 9.6, 10.2,
10.3, 10.3, 10, 10, 10.1, 10.4, 10.6, 9.7), MYH1 = c(4.7, 4.7,
4.7, 4.7, 4.7, 4.7, 4.7, 4.7, 4.7, 5, 4.7, 4.7, 4.7, 5, 4.7,
4.7, 4.7, 5, 4.7, 4.7, 4.7), KLF3 = c(10.4, 10.5, 10.4, 10.7,
10.4, 10.6, 10.4, 10.6, 10.2, 10.4, 10.5, 10.5, 10.7, 10.6, 10.8,
10.7, 10.3, 10.7, 10.8, 10.7, 10.2), PPARGC1A = c(5.4, 5.2, 4.7,
5.1, 5.4, 5.1, 5.6, 5.1, 5.1, 5.3, 4.7, 5.5, 4.7, 5.1, 5.2, 5.1,
5.4, 5.2, 5.2, 5, 5), CCND1 = c(11.3, 11, 11.1, 11.9, 10.5, 11.8,
12.4, 12, 12.7, 12.4, 11.6, 11.4, 12.1, 11.7, 11.4, 11.6, 11.9,
11.5, 10.9, 11.9, 12.1), ATP5F1B = c(13.3, 13.1, 13.2, 13.1,
13.1, 13.1, 13.2, 12.9, 13.6, 13.3, 13.1, 13.5, 13.1, 13.1, 13,
13.1, 13.1, 13.2, 13.1, 13, 12.9), LDHB = c(9.3, 8.7, 8.6, 9.5,
7.6, 8.5, 9.1, 9, 10.4, 8.9, 9.2, 9.6, 9.4, 9, 8.5, 9.1, 8.8,
8.7, 8.4, 8.6, 9.2), PRKAB1 = c(10, 9.7, 9.6, 9.8, 9.8, 10, 10,
9.7, 9.8, 10, 9.7, 10.1, 9.7, 9.7, 10.1, 10, 10, 9.9, 9.9, 9.8,
10.2), CCND3 = c(11.3, 11, 11.1, 11.1, 11, 11.3, 11.1, 10.9,
11.8, 11.7, 11.4, 11.8, 11.4, 11.2, 11.3, 11, 11.2, 11, 10.9,
11.1, 10.9), SRF = c(10.8, 10.6, 10.1, 10.7, 10.6, 10.5, 10.3,
10, 10.5, 11, 10.3, 10.7, 10.9, 10.3, 10.8, 10.5, 10.9, 10.7,
10.2, 10.2, 10.5), VEGFA = c(10.6, 10.4, 10.6, 11, 10.4, 11.4,
9.3, 9.2, 8.7, 9.4, 11.8, 12, 9.5, 10.3, 9.5, 12.1, 9.8, 9.6,
10.8, 9.3, 9.2), SMAD5 = c(9.8, 9.8, 9.8, 10.1, 9.7, 9.9, 10,
10.1, 10.1, 9.7, 10.3, 9.9, 9.9, 9.9, 9.7, 10.3, 9.8, 9.8, 9.7,
9.9, 9.8), HES1 = c(9.9, 10.6, 10.1, 9.8, 10.7, 10.3, 9.5, 10.3,
9.7, 10.4, 9.1, 9, 9.9, 10.2, 10.6, 9.5, 10, 10, 9.9, 10.6, 10.7
), GLS = c(9.3, 9.4, 9.5, 9.8, 9.3, 9.3, 9.9, 10, 9.8, 9.8, 9.5,
9.8, 9.6, 10.2, 10, 9.9, 9.6, 9.6, 9.5, 9.8, 9.6), KDM5B = c(11.4,
11.5, 11.6, 10.9, 11.5, 11.3, 10.9, 11, 10.8, 10.9, 10.9, 10.7,
11.1, 11.1, 11.4, 10.9, 11.3, 11.3, 11.6, 11.4, 11), STMN1 = c(11.3,
10.6, 11.2, 11, 11, 10.8, 11.4, 11.5, 12.1, 11.2, 11.2, 11.7,
11.2, 11.1, 10.7, 10.8, 11.1, 11.2, 11.1, 10.8, 11), ATF6 = c(11.3,
11.2, 11.4, 10.9, 11.2, 11.3, 11.1, 11, 10.9, 11.2, 10.9, 11,
11.1, 11.2, 11.2, 11.1, 11.3, 11.2, 11.5, 11.4, 10.7), MYB = c(6,
6.1, 5.8, 6.1, 6, 5.8, 6.5, 6.1, 6.7, 6, 6, 6.3, 5.9, 6.2, 5.7,
5.8, 5.9, 6.1, 5.7, 5.7, 5.8), FOXO3 = c(9.9, 9.6, 10.5, 9.6,
9.5, 9.8, 9.2, 9.3, 8.9, 9.2, 10.1, 10.2, 9.4, 9.4, 9.3, 9.8,
9.1, 10.3, 10.4, 9.2, 9.3), NEK6 = c(9.3, 9.5, 9.4, 9.9, 9.5,
9.5, 9.8, 9.9, 9.8, 9.7, 9.7, 9.8, 10, 10.2, 10.2, 10.1, 9.7,
9.4, 9.1, 9.8, 9.8), DNMT3A = c(11.8, 11.9, 11.7, 11.4, 11.9,
11.7, 11.6, 11.5, 11.3, 11.7, 11.4, 10.9, 11.8, 11.6, 11.5, 11.4,
11.5, 11.6, 11.8, 11.7, 11.9), DUSP1 = c(12.6, 13.3, 12.3, 12.2,
13.1, 12.9, 12, 12.1, 11.8, 12.9, 12.2, 12.6, 13.1, 12.7, 13.5,
12.8, 13.1, 12.6, 13, 13.8, 13.1), SOCS2 = c(10.5, 10.3, 10.6,
10.2, 10.1, 10.1, 10.1, 10, 9.8, 10.4, 10.3, 10, 10.6, 10, 10.2,
10.4, 9.9, 10.4, 11.3, 10.1, 10.2), APAF1 = c(8.8, 8.7, 8.8,
9.2, 8.4, 8.9, 9.1, 9, 9, 8.7, 9, 9.1, 9, 8.9, 8.7, 9.1, 8.2,
9, 8.9, 8.8, 8.5), ATXN1 = c(9, 9.5, 9.2, 9.9, 8.7, 9.4, 9.3,
9.5, 9.4, 9.9, 9.8, 9.4, 9.2, 9.2, 9, 9.6, 9.3, 9, 8.8, 9.3,
9.2), MT2A = c(9.9, 8.6, 9.9, 9.7, 9.3, 9, 9.7, 9.4, 10.5, 9.7,
9.9, 11.3, 9.3, 9, 9.4, 9.4, 9.6, 9.8, 9.6, 9, 9.3), IRF1 = c(10.7,
10.5, 10.6, 10, 10.9, 10.4, 10.1, 10.3, 9.8, 10.1, 10, 9.7, 10.2,
9.9, 10.4, 10.2, 10.5, 10.1, 10.2, 10.3, 10.5), SOX9 = c(5.4,
5.3, 5, 5.5, 5.9, 5, 5.7, 5.1, 5.1, 4.7, 5.4, 5.8, 4.7, 5.3,
5.3, 5.6, 5.9, 5.4, 5.4, 5.4, 5.2), MYH2 = c(5.1, 5, 5, 5.2,
4.7, 4.7, 5.2, 5.4, 5, 5.7, 5, 5, 4.7, 4.7, 5.3, 5, 5.2, 4.7,
4.7, 5.3, 5.4), RAP1B = c(8.8, 8.9, 9.1, 8.8, 9.1, 8.8, 8.8,
8.9, 8.7, 8.7, 8.6, 8.5, 9, 9.1, 8.9, 8.7, 8.9, 8.9, 9.1, 9,
8.6), FOXA1 = c(5.1, 5.1, 4.7, 4.7, 5.3, 5, 5.1, 5.4, 5.1, 5,
4.7, 5.1, 5.1, 5.1, 5, 5.1, 5, 4.7, 5.1, 5, 4.7), ATG4D = c(9.3,
9.2, 9.2, 9, 9.2, 9.1, 9.1, 9, 9.1, 9.1, 9.2, 8.9, 9.1, 8.9,
8.9, 9.2, 9.2, 9.2, 9.3, 9.1, 9.4), G6PC1 = c(4.7, 4.7, 5.1,
4.7, 4.7, 4.7, 4.7, 5, 5.1, 4.7, 4.7, 4.7, 5, 5, 5, 5, 5.1, 5,
4.7, 5, 5), GRSF1 = c(10.5, 10.4, 10.4, 10.4, 10.4, 10.3, 10.4,
10.5, 10.8, 10.6, 10.5, 10.5, 10.5, 10.6, 10.3, 10.5, 10.6, 10.5,
10.5, 10.5, 10.2), TERF2 = c(9.4, 9.3, 9.4, 9.2, 9.3, 9.3, 9.1,
9.2, 9.4, 9.4, 9.3, 9.2, 9.1, 9.2, 9.4, 9.2, 9.2, 9.4, 9.2, 9.3,
9.1), CDK8 = c(8.5, 8.6, 8.9, 8.7, 8.6, 8.7, 8.4, 8.5, 8.7, 8.7,
8.9, 8.8, 8.7, 8.6, 8.5, 8.6, 8.7, 8.8, 8.9, 8.6, 8.1), VHL = c(10.2,
10, 10, 10, 10, 10, 10, 10, 10.1, 10.1, 10, 9.9, 10.1, 10.1,
10.1, 10, 10.2, 10, 10.2, 10.3, 10), MYCN = c(8.3, 7.8, 7.9,
8, 8.5, 8, 8.6, 8.1, 8.7, 8.5, 8.2, 7.7, 8.5, 8, 8.4, 8.5, 9.1,
8.1, 7.4, 8.1, 8.5), LDHA = c(11.2, 10.8, 11, 11.7, 11.1, 11.3,
11.7, 11.5, 12.3, 11.8, 11.4, 11.7, 11.6, 11.5, 11.9, 11.2, 11.7,
10.9, 10.6, 11.2, 11.1), SPRY2 = c(8.9, 8.9, 9.3, 8.8, 8.7, 8.9,
8.8, 8.9, 9, 9, 9.1, 9.2, 8.9, 8.6, 8.6, 8.9, 8.9, 8.8, 9, 8.8,
8.6), RAC1 = c(11.9, 11.7, 11.9, 11.8, 11.7, 11.8, 11.7, 11.8,
12.2, 11.8, 11.9, 12, 11.8, 11.8, 11.8, 11.9, 11.9, 11.8, 11.9,
11.7, 11.7), PIM1 = c(11.5, 11.6, 11.8, 10.8, 11.9, 11.6, 11.3,
11, 11, 11.3, 11.1, 10.3, 11.5, 11, 11.3, 11, 11.7, 11.3, 12.2,
11.9, 11.3), ATAT1 = c(10.6, 10.6, 10.5, 10.5, 10.6, 10.5, 10.8,
10.8, 10.7, 10.9, 10.7, 10.7, 10.7, 10.5, 10.5, 10.6, 10.4, 10.7,
10.1, 10.3, 10.7), KIF23 = c(9, 7.8, 8.6, 8.6, 8.8, 8.5, 9.4,
9.1, 9.9, 9.1, 8.8, 9.6, 9, 8.9, 9, 8.2, 9, 9, 8.4, 8.7, 8.5),
FGF2 = c(6.9, 7.4, 7.5, 7.9, 7, 7.3, 7.8, 7.5, 7.3, 7.6,
7.9, 6.8, 7.2, 7.4, 7.9, 7.5, 7.3, 7.1, 7.3, 7.2, 7.3), APP = c(14.3,
14, 14.4, 13.9, 13.7, 14, 14, 14, 14.4, 13.9, 14.5, 14.5,
14, 14, 13.8, 14.2, 14.1, 14.1, 14, 14, 14), RGS5 = c(8.9,
8.1, 8.1, 9.1, 8.4, 8.6, 10.1, 9.5, 9, 9.4, 9.2, 9.2, 9.8,
9.1, 8.1, 7.9, 9.7, 10.5, 7.5, 8.9, 8.9)), row.names = c("Control1",
"Control2", "Control3", "Control4", "Control5", "Control6", "Control7",
"Control8", "Control9", "Control10", "Control11", "Control12",
"Control13", "Control14", "Control15", "Control16", "Control17",
"Control18", "Control19", "Control20", "Control21"), class = "data.frame")
I tried adjusting the width and height parameters in the png() function, but it didn't make a noticeable difference.
png("correlation_plot.png", width = 800, height = 600)
..code..
dev.off()
How can I make the plot more clear and readable?
Solution
80 columns is a bit much for anyone to visualise, unless you are making a poster. For A4-size paper, you may need to split the columns in half, and reduce the size of the text using the cex arguments:
cor_col <- colorRampPalette(c("green", "grey", "darkorange"))
M_1 = c_df$r[1:3, 4:40]
p.mat_1 = c_df$P[1:3, 4:40]
M_2 = c_df$r[1:3, 41:80]
p.mat_2 = c_df$P[1:3, 41:80]
cex <- 0.6
opar <- par(mfrow=c(2,1))
corrplot(M_1, method="color", col=cor_col(10), addCoef.col = "black", tl.col="black",
p.mat = p.mat, sig.level = 0.05, insig = "blank", diag=FALSE,
tl.cex = cex, cl.cex=cex, number.cex = cex)
corrplot(M_2, method="color", col=cor_col(10), addCoef.col = "black", tl.col="black",
p.mat = p.mat_2, sig.level = 0.05, insig = "blank", diag=FALSE,
tl.cex = cex, cl.cex=cex, number.cex = cex)
par(opar)
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