Question

我想在R中针对以下示例数据帧“数据”执行两次样本Kolmogorov-Smirnov（KS）测试：

    Protein1    Protein2    Protein3    Protein4    Protein5    Protein6    Protein7    Protein8    Group
Sample1 0.56    1.46    0.64    2.53    1.96    305.29  428.41  113.22  Control
Sample2 0.75    2.29    0.38    4.31    1.72    307.95  492.58  82.75   Control
Sample3 2.05    1.73    2.42    14.75   2.92    523.92  426.94  131.51  Control
Sample4 1.71    5.37    0.68    6.39    2.02    343.05  435.16  123.12  Control
Sample5 13.31   0.94    1.21    3.83    2.83    313.71  327.84  66.8    Control
Sample6 0.36    1.81    0.42    2.25    1.48    335.23  352.55  93.81   Control
Sample7 0.28    3.26    0.49    2.62    1.96    251.49  468.19  80.27   Control
Sample8 1.62    17.01   0.49    2.87    1.7 254.79  402.9   86.8    Control
Sample9 0.59    2.64    0.18    2.93    1.23    388.87  384.53  109.52  Control
Sample10    1.67    3.75    0.43    3.89    1.83    306.28  440.86  97.55   Control
Sample11    15.53   12.02   0.57    1.81    2.31    328.56  352.98  118.18  Control
Sample12    0.94    7.06    35.77   4.98    2.44    389.14  376.18  119.75  Control
Sample13    2.07    1.73    0.38    3.89    2.56    233.81  377.21  72.1    Control
Sample14    3.2 1.38    0.5 4.05    2.51    406.57  538.57  209.16  Patient
Sample15    1.33    2.17    0.46    3.31    1.72    278.04  276.37  79.4    Patient
Sample16    1.48    2.9 0.84    9.27    1.94    332.76  413.66  99.09   Patient
Sample17    2.02    1.96    0.25    4.16    1.96    358.73  383.63  107.46  Patient
Sample18    2.94    2   0.27    3.99    2.55    354.78  493.02  145.36  Patient
Sample19    1.01    8.1 0.35    3.65    1.62    335.18  264.74  145.15  Patient
Sample20    6.95    15.48   2.94    3.64    2.3 307.23  484.38  119.61  Patient
Sample21    0.52    1.38    0.56    3.08    1.86    244.3   304.74  76.87   Patient
Sample22    0.35    2.17    0.38    4.51    2.09    304.68  369.98  151.76  Patient
Sample23    2.26    2.9 0.3 4.44    2.43    302.51  367.51  150.69  Patient
Sample24    3.19    1.96    0.81    2.94    2.15    309.59  362.18  133.49  Patient
Sample25    1.12    2   0.71    3.77    2.42    334.36  358.9   131.35  Patient
Sample26    5.28    8.1 0.81    22.84   2.35    422.18  369.71  76.35   Patient

要在两列之间执行KS测试，这是代码：

> ks.test(data$Protein1, data$Protein2, data=data)

    Two-sample Kolmogorov-Smirnov test

data:  data$Protein1 and data$Protein2
D = 0.42308, p-value = 0.01905
alternative hypothesis: two-sided

Warning message:
In ks.test(data$Protein1, data$Protein2, data = data) :
  cannot compute exact p-value with ties

但是，我想按列和按组进行此操作。例如，对于t.test或wilcox.test来说很容易做到这一点，因为您可以将代码编写为 t.test（y1，y2）或t.test（y〜x）＃其中y是数字且x是二进制因子但是涉及二进制因子时，ks.test没有代码。有人可以帮忙吗？

最终，我想对所有蛋白质的整个数据框都执行此操作，就像我可以成功完成t检验一样，但是想要对ks.test进行如下操作：

t_tests <- lapply(
  data[, -1], # apply the function to every variable *other than* the first one (group)
  function(x) { t.test(x ~ HealthGroups, data = data) }
)

任何帮助表示赞赏。预先谢谢你。

Answer 1

这是一种非常简单的方法。这使用了一个循环，通常在R圈中会皱眉。但是，它非常简单且不言自明，对于较新的用户可能是一个加分，并且在这种情况下循环过慢也没有问题。（请注意，您可以根据需要使用lapply()进行此操作，但这仍然是一个循环，在外观上看起来有所不同。）

只需创建两个具有相同变量的新的子集数据帧。然后循环调用ks.test的数据帧。输出的结果不是非常用户友好-它只会显示j-因此我向?writeLines添加了一个调用以打印被测试变量的名称。

# I am assuming the original data frame is called d
dc <- d[d$Group=="Control",]
dp <- d[d$Group=="Patient",]
for(j in 1:8){  
  writeLines(names(dc)[j])
  print(ks.test(dc[,j], dp[,j]))  
}
# Protein1
# 
#   Two-sample Kolmogorov-Smirnov test
# 
# data:  dc[, j] and dp[, j]
# D = 0.30769, p-value = 0.5882
# alternative hypothesis: two-sided
# 
# Protein2
# 
#   Two-sample Kolmogorov-Smirnov test
# 
# data:  dc[, j] and dp[, j]
# D = 0.23077, p-value = 0.8793
# alternative hypothesis: two-sided
# 
# Protein3
# 
#   Two-sample Kolmogorov-Smirnov test
# 
# data:  dc[, j] and dp[, j]
# D = 0.23077, p-value = 0.8793
# alternative hypothesis: two-sided
# 
# Protein4
# 
#   Two-sample Kolmogorov-Smirnov test
# 
# data:  dc[, j] and dp[, j]
# D = 0.46154, p-value = 0.1254
# alternative hypothesis: two-sided
# 
# Protein5
# 
#   Two-sample Kolmogorov-Smirnov test
# 
# data:  dc[, j] and dp[, j]
# D = 0.23077, p-value = 0.8793
# alternative hypothesis: two-sided
# 
# Protein6
# 
#   Two-sample Kolmogorov-Smirnov test
# 
# data:  dc[, j] and dp[, j]
# D = 0.15385, p-value = 0.9992
# alternative hypothesis: two-sided
# 
# Protein7
# 
#   Two-sample Kolmogorov-Smirnov test
# 
# data:  dc[, j] and dp[, j]
# D = 0.38462, p-value = 0.2999
# alternative hypothesis: two-sided
# 
# Protein8
# 
#   Two-sample Kolmogorov-Smirnov test
# 
# data:  dc[, j] and dp[, j]
# D = 0.46154, p-value = 0.1265
# alternative hypothesis: two-sided
# 
# Warning messages:
# 1: In ks.test(dc[, j], dp[, j]) : cannot compute exact p-value with ties
# 2: In ks.test(dc[, j], dp[, j]) : cannot compute exact p-value with ties
# 3: In ks.test(dc[, j], dp[, j]) : cannot compute exact p-value with ties
# 4: In ks.test(dc[, j], dp[, j]) : cannot compute exact p-value with ties

这将创建一个数据框来容纳结果：

dk <- data.frame(Protein=character(8), D=numeric(8), p=numeric(8), stringsAsFactors=F)
for(j in 1:8){  
  k <- ks.test(dc[,j], dp[,j])
  dk$Protein[j] <- names(dc)[j]
  dk$D[j]       <- k$statistic
  dk$p[j]       <- k$p.value
}
dk
#    Protein         D         p
# 1 Protein1 0.3076923 0.5881961
# 2 Protein2 0.2307692 0.8793244
# 3 Protein3 0.2307692 0.8793244
# 4 Protein4 0.4615385 0.1253895
# 5 Protein5 0.2307692 0.8793244
# 6 Protein6 0.1538462 0.9992124
# 7 Protein7 0.3846154 0.2999202
# 8 Protein8 0.4615385 0.1264877

如何按组在R中的数据框中执行KS.test

1 个答案: