在个人列之间的R和在给定数据帧的其余部分进行t检验 [英] t-test in R between individuals columns and the rest of a given dataframe

问题描述

这是在R.我需要帮助采取基本格式的数据框

This is in R. I need help taking a dataframe of basic format

       NAC     cOF3     APir       Pu       Tu     V2.3     mOF3     DGpf
1 6.314770 6.181188 6.708971 6.052134 6.546938 6.079848 6.640716 6.263770
2 8.825595 8.740217 9.532026 8.919598 8.776969 8.843287 8.631505 9.053732
3 5.518933 5.982044 5.632379 5.712680 5.655525 5.580141 5.750969 6.119935
4 6.063098 6.700194 6.255736 5.124315 6.133631 5.891009 6.070467 6.062815
5 8.931570 9.048621 9.258875 8.681762 8.680993 9.040971 8.785271 9.122226
6 5.694149 5.356218 5.608698 5.894171 5.629965 5.759247 5.929289 6.092337

，并简化了对列进行t检验与所有其他列组合的任务。我也需要p值，我打算通过一些变化得到：

and streamlining the task of taking a t-test of every column versus all the other columns combined. I also will need the p-values, which I plan to get via some variation on:

#t-test
test.result = mapply(t.test, select.column, other.columns)
#store p-values
p.values = stack(mapply(function(x, y) t.test(x,y)$p.value, select.column, other.columns))

或者将aov （）作为这样一个分析的更好的选择？

Or would aov() be a better alternative for such an analysis?

推荐答案

sapply(names(dat), function(x) 
         sapply( names(dat), function(y) t.test(dat[[x]],dat[[y]])$statistic ))

可以使用函数t.test在列表中返回的任何值。也可以遍历 combn（names（dat），2）的结果，这将是一个 choose（n，2）矩阵。 （方阵具有明显的冗余结果）显然需要对多次测试进行明智的调整。可以使用 p.adjust 。

Can use any of the values returned in the list from the function t.test. Could also have looped across the results of combn(names(dat), 2), which would be a choose(n,2) matrix. (The square matrix has obvious redundant results) Obviously need a sensible adjustment for multiple testing. Could use p.adjust.

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