从相关矩阵中找出具有良好相关性的基因

Question

我有矩阵文件，它基本上是跨各种细胞类型的基因之间的spearman相关矩阵。所以现在我试图找出哪些基因或基因组的相关值可以说大于0.6，如​​果我将其设置为我的阈值。我怎样才能做到这一点？我正在发布我的数据子集。它是一个502 x 502矩阵。

        ACTL6B   ACTR5   ACTR6
ACTL6B  1        0.6        -0.4
ACTR5   0.4        1        -0.3
ACTR6  -0.4      -0.3         1

所以我不希望相同的基因组之间的相关性是1.我想要另一个比较。比方说，ACTL6B和ACTR5的相关系数为0.6。我想保留这些价值观和基因。

Answer 1

以下是一个例子：

mat <- cor(longley)  # example 7 x 7 correlation matrix

# Find indices of correlations greater than 0.6
idx <- which(mat > 0.6 & lower.tri(mat), arr.ind = TRUE)

# names of the resulting variables
cbind(rownames(idx), colnames(mat)[idx[, 2]])

由于lower.tri，对角线和上矩阵中的所有值都将被忽略。

结果：

      [,1]         [,2]          
 [1,] "GNP"        "GNP.deflator"
 [2,] "Unemployed" "GNP.deflator"
 [3,] "Population" "GNP.deflator"
 [4,] "Year"       "GNP.deflator"
 [5,] "Employed"   "GNP.deflator"
 [6,] "Unemployed" "GNP"         
 [7,] "Population" "GNP"         
 [8,] "Year"       "GNP"         
 [9,] "Employed"   "GNP"         
[10,] "Population" "Unemployed"  
[11,] "Year"       "Unemployed"  
[12,] "Year"       "Population"  
[13,] "Employed"   "Population"  
[14,] "Employed"   "Year"