对数据集中每一行的列进行t.test [英] doing t.test for columns for each row in data set

问题描述

我有一组数据x，它由12列和167行组成.第一列是每一行的复合ID.我想分别为每行分别将3列的t.test作为一组运行，将其他3组作为第二组运行.我的代码如下，但不起作用.

I have a set of data x which consists of 12 columns and 167 rows. The first column is compound Id for each row. I want to run a t.test for 3 column as one group and the other 3 groups as the second group, separately for each row. My code is as below but it does not work.

for (i in 1:nrow(x)) {
 function(i)c(compound=i,
    t.test(x[2:4],x[8:10],
      x[x$compound==i, ],
      alternative='two.sided',conf.level=0.95)
    )
}
print(c(compound=i,t.test(x[2:4],x[8:10],x[x$compound==i,],
    alternative='two.sided',conf.level=0.95)))

我的目的是对AC组和SC组之间的每种代谢物(化合物)进行t.test，这是两组细胞.

My intention was doing a t.test for each metabolite (compound) between AC groups and SC groups, these are two group of cells.

compound    AC-1     AC-2     AC-3     AM-1      AM-2      AM-3      SC-1     SC-2     SC-3     SM-1      SM-2      SM-3
alanine     27612820 22338050 15359640 19741350  18726880  18510800  10914980 12071660 16036180 16890860  16066960  16364300
arginine    7067206  7172234  5933320  136272600 131596800 134717600 6102838  7186256  6770344  140127100 155341300 151748000
asparagine  3151398  2141378  1240904  11522180  8907711   9842342   1677299  2265826  2942991  11690360  12552660  12102620                        

推荐答案

另一种替代方法是使用软件包.

Another alternative is using a package.

您的数据:

df <- rbind(c(27612820, 22338050, 15359640, 19741350, 18726880, 18510800, 10914980, 12071660, 16036180, 16890860, 16066960, 16364300),
        c(7067206, 7172234, 5933320, 136272600, 131596800, 134717600, 6102838, 7186256, 6770344, 140127100, 155341300, 151748000),
        c(3151398, 2141378, 1240904, 11522180, 8907711, 9842342, 1677299, 2265826, 2942991, 11690360, 12552660, 12102620)
        )

df <- data.frame(df)
rownames(df) <- c("alanine", "arginine", "asparagine")
colnames(df) <- c("AC-1", "AC-2", "AC-3", "AM-1", "AM-2", "AM-3", "SC-1", "SC-2", "SC-3", "SM-1", "SM-2", "SM-3")

然后对AC组和SC组之间的每一行进行t检验:

Then to run a t-test on every row between AC and SC groups:

library(matrixTests)
> row_t_welch(df[,c("AC-1", "AC-2", "AC-3")], df[,c("SC-1", "SC-2", "SC-3")])
           obs.x obs.y obs.tot   mean.x   mean.y mean.diff          var.x         var.y    stderr       df   statistic    pvalue conf.low conf.high alternative mean.null conf.level
alanine        3     3       6 21770170 13007607 8762563.3 37776970798900 7213669482133 3872580.5 2.736945  2.26271945 0.1171389 -4259692  21784819   two.sided         0       0.95
arginine       3     3       6  6724253  6686479   37774.0   471939373529  298723602417  506840.9 3.807645  0.07452832 0.9443398 -1397926   1473474   two.sided         0       0.95
asparagine     3     3       6  2177893  2295372 -117478.7   913496858185  401148784303  661978.3 3.472571 -0.17746605 0.8690016 -2070931   1835973   two.sided         0       0.95

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