R 水平数据帧中三重数据的t检验

我正在尝试做一个循环，这样我就可以测试多个条件：cond_a、cond_B和cond_C，每个条件都针对同一个控件（“ctrl”）。每个条件和控件由三份副本表示。作为结果，我希望得到一个带有条件名称和pvalues的数据帧

以下是我的意见：

structure(list(ctrl_1 = 1L, ctrl_2 = 2L, ctrl_3 = 3L, cond_A_1 = 4L, 
    cond_A_2 = 4L, cond_A_3 = 4L, cond_B_1 = 5L, cond_B_2 = 5L, 
    cond_B_3 = 7L, cond_C_1 = 8L, cond_C_2 = 9L, cond_C_3 = 2L), .Names = c("ctrl_1", 
"ctrl_2", "ctrl_3", "cond_A_1", "cond_A_2", "cond_A_3", "cond_B_1", 
"cond_B_2", "cond_B_3", "cond_C_1", "cond_C_2", "cond_C_3"), class = "data.frame", row.names = c(NA, 
-1L))

以及假设PV值的预期输出：

cond_A_pval cond_B_pval cond_C_pval
0.05    0.9 0.006

以下是我的出发点：

pval<-apply(df,1,function(x) {t.test(x[1:3],x[4:6])$p.value})

pval尝试以下操作：

df <- structure(list(ctrl_1 = 1L, ctrl_2 = 2L, ctrl_3 = 3L, cond_A_1 = 4L, 
               cond_A_2 = 4L, cond_A_3 = 4L, cond_B_1 = 5L, cond_B_2 = 5L, 
               cond_B_3 = 7L, cond_C_1 = 8L, cond_C_2 = 9L, cond_C_3 = 2L), 
               .Names = c("ctrl_1", "ctrl_2", "ctrl_3", 
                          "cond_A_1", "cond_A_2", "cond_A_3", 
                          "cond_B_1", "cond_B_2", "cond_B_3", 
                          "cond_C_1", "cond_C_2", "cond_C_3"), 
               class = "data.frame", row.names = c(NA, -1L))

library(tidyr)

# Reshape the data into key-value pairs. 
# It is generally advisable to have data in tidy format. 
df <- gather(df)
# Remove the _1, _2, etc. 
df$group <- gsub("_\\d", "", df$key)

#Now you can loop through the groups. Note that "ctrl" is the first group:
sapply(unique(df$group)[-1], function(x){
  t.test(df[df$group == "ctrl", "value"], df[df$group == x, "value"])$p.value 
})

 cond_A     cond_B     cond_C 
0.07417990 0.01477836 0.17957429 

df使用示例中的值，但不使用我的真实数据，见下文；结构（列表）（键=c（“ctrl_1”、“ctrl_2”、“ctrl_3”、“cond_A_1”、“cond_A_2”、“cond_A_3”、“cond_B_1”、“cond_B_2”、“cond_B_3”、“cond_c_1”、“cond_A_2”、“cond_A_2”、“cond_A_3”）、值=c（“13.382”、“12.9152”、“14.719”、“13.3822”、“12.9152”、“8.788”、“9.3765”、“17.4”、“1526.5”、“cond_2”、“c_2”、“c_3”）、“c组”、“ctrl=c”，“cond_A”，“cond_A”，“cond_B”，“cond_B”，“cond_B”，“cond_C”，“cond_C”，“cond_C”），.Names=C（“key”，“value”，“group”），row.Names=C（NA，-12L），class=“data.frame”）包括：dft这似乎是基础数据的问题。在
结构中，这些值被指定为字符（字符串）。很高兴它在将数据转换为数字后工作。知道如何以类似的方式从方差分析中获得pval“Pr（>F）”吗？使用（df，aov（value~group））