从R中的数据帧计算平均成对Pearson相关系数

Question

假设我有以下向量：

IDs_Complex_1 <- c("orangutan", "panda", "sloth", "mountain_gorilla", "dolphin", "snake")
IDs_Complex_2 <- c("bat", "penguin", "goat", "elephant", "tiger")

我想计算组织列中垂直获取的值之间的成对 Pearson 相关系数，对于每个向量，在以下数据框中。然后我希望找到所有可能组合的平均 PCC。

 Complex_ID        Tissue_X Tissue_Y Tissue_Z
 orangutan         5         6        7
 panda             6         7        8
 sloth             7         8        9
 mountain_gorilla  100       60       50
 dolphin           115       62       51
 snake             130       59       67
 bat               2         6        7
 penguin           15        11       12
 goat              22        23       86
 elephant          14        22       109
 tiger             0         1        7

为了说明复数 1，我想计算：

  PCC_1 <- PCC of (5, 6, 7, 100, 115, 130) and (6, 7, 8, 60, 62, 59)
  PCC_2 <- PCC of (5, 6, 7, 100, 115, 130) and (7, 8, 9, 50, 51, 67)
  PCC_3 <- PCC of (6, 7, 8, 60, 62, 59) and (7, 8, 9, 50, 51, 67)

我想计算

的平均值

  (PCC_1, PCC_2, PCC_3) = ?

但是，如果我有大约 20 个组织柱，而那里会有 20!/2!18！ = 成对相关系数的 190 种组合（无重复）。我将如何编码？

非常感谢！

阿比盖尔

Answer 1

如果 df 是你的 data.frame:

df = structure(list(Complex_ID = structure(c(6L, 7L, 9L, 5L, 2L, 10L, 
1L, 8L, 4L, 3L, 11L), .Label = c("bat", "dolphin", "elephant", 
"goat", "mountain_gorilla", "orangutan", "panda", "penguin", 
"sloth", "snake", "tiger"), class = "factor"), Tissue_X = c(5L, 
6L, 7L, 100L, 115L, 130L, 2L, 15L, 22L, 14L, 0L), Tissue_Y = c(6L, 
7L, 8L, 60L, 62L, 59L, 6L, 11L, 23L, 22L, 1L), Tissue_Z = c(7L, 
8L, 9L, 50L, 51L, 67L, 7L, 12L, 86L, 109L, 7L)), class = "data.frame", row.names = c(NA, 
-11L))

你可以这样做：

    cor(df[,-1])
          Tissue_X  Tissue_Y  Tissue_Z
Tissue_X 1.0000000 0.9748668 0.4119840
Tissue_Y 0.9748668 1.0000000 0.5440719
Tissue_Z 0.4119840 0.5440719 1.0000000

从R中的数据帧计算平均成对Pearson相关系数

Calculating average pairwise Pearson Correlation Coefficients from Data Frame in R

combinations

average

r

dataframe

pearson-correlation