avoid within table correlations in rcorr

Question

[Edalat]

I´m building a correlation between two different matrices(coding-lncoding) with rcorr() function in R,how can I remove within table correlations?is there any way or I should remove them by hand?

[Biomonika (Noolean)]

What specifically do you call within table correlation?

[Edalat]

see this table that made by another person:

table1 <- matrix(rnorm(25),5)

table2 <- matrix(rnorm(25),5)

res <- rcorr(table1, table2, type="pearson") res

       [,1]  [,2]  [,3]  [,4]  [,5]  | [,6]  [,7]  [,8]  [,9] [,10]
# [1,]  1.00 -0.55  0.95 -0.16  0.17 |-0.46  0.15  0.10  0.69  0.16
# [2,] -0.55  1.00 -0.55 -0.60 -0.79 |-0.45 -0.66 -0.22 -0.30  0.12
# [3,]  0.95 -0.55  1.00 -0.09  0.30 |-0.35 -0.05 -0.17  0.57 -0.03
# [4,] -0.16 -0.60 -0.09  1.00  0.91 | 0.92  0.53 -0.21 -0.58 -0.71
# [5,]  0.17 -0.79  0.30  0.91  1.00 | 0.78  0.41 -0.31 -0.32 -0.68
# ------------------------------------------------------------------
# [6,] -0.46 -0.45 -0.35  0.92  0.78 | 1.00  0.44 -0.14 -0.62 -0.58
# [7,]  0.15 -0.66 -0.05  0.53  0.41 | 0.44  1.00  0.68  0.13  0.13
# [8,]  0.10 -0.22 -0.17 -0.21 -0.31 |-0.14  0.68  1.00  0.59  0.80
# [9,]  0.69 -0.30  0.57 -0.58 -0.32 |-0.62  0.13  0.59  1.00  0.80
#[10,]  0.16  0.12 -0.03 -0.71 -0.68 |-0.58  0.13  0.80  0.80  1.00
# pvalues to follow ...

Notice the upper right quadrant of rcorr() (which repeats diagonally symmetrical on lower left) is the entire result of cor() (rounded to two decimal points)

res <- cor(table1, table2, method="pearson")

res

#            [,1]        [,2]       [,3]       [,4]        [,5]
# [1,] -0.4551474  0.15080994  0.1008215  0.6894955  0.16390813
# [2,] -0.4468285 -0.66209106 -0.2154960 -0.2954581  0.11662382
# [3,] -0.3542023 -0.05474287 -0.1720881  0.5669501 -0.02880113
# [4,]  0.9246330  0.53456574 -0.2084105 -0.5807386 -0.71108552
# [5,]  0.7788395  0.40551828 -0.3122606 -0.3209273 -0.67912147

I want the correlation like core result,I need p-value so I used rcorr() function.

Answer 1

[jpgsabino]

Hello,

You can try this:

table1 <- matrix(rnorm(25),5)

table2 <- matrix(rnorm(25),5)

cor.matrix <- rcorr(table1, table2, type="pearson")

P <- data.frame(cor.matrix$P)
R <- data.frame(cor.matrix$r)

# Data frame with p values
P.df <- P[,-c(1:ncol(table1))]
P.df <- P.df[-c((ncol(table1))+1:ncol(P)),]
P.df

# Data frame with r values
R.df <- R[,-c(1:ncol(table1))]
R.df <- R.df[-c((ncol(table1))+1:ncol(R)),]
R.df

Grts