paired t-test with pairs and groups defined in another dataframe

问题

I have a dataframe which looks like this

> head(data)
               LH3003     LH3004     LH3005     LH3006     LH3007     LH3008     LH3009     LH3010     LH3011
cg18478105 0.02329879 0.08103364 0.01611778 0.01691191 0.01886975 0.01885553 0.01647439 0.02120779 0.01168622
cg14361672 0.09479536 0.07821380 0.02522833 0.06467310 0.05387729 0.05866673 0.08121820 0.10920162 0.04413263
cg01763666 0.03625680 0.04633759 0.04401555 0.08371531 0.09866403 0.17611284 0.07306743 0.12422579 0.11125146
cg02115394 0.10014794 0.09274320 0.08743445 0.08906313 0.09934032 0.18164115 0.06526380 0.08158144 0.08862067
cg13417420 0.01811630 0.02221060 0.01314041 0.01964530 0.02367295 0.01209913 0.01612864 0.01306061 0.04421938
cg26724186 0.32776266 0.31386294 0.24167480 0.29036142 0.24751268 0.26894756 0.20927278 0.28070790 0.33188921
               LH3012     LH3013     LH3014
cg18478105 0.02466508 0.01909706 0.02054417
cg14361672 0.09172160 0.06170230 0.07752691
cg01763666 0.04328518 0.13693868 0.04288165
cg02115394 0.08682942 0.08601880 0.12413149
cg13417420 0.01980470 0.02241745 0.02038114
cg26724186 0.30832389 0.27644816 0.37630038

with almost 850000 rows, and a different dataframe which contains the information behind the sample names:

> variables
   Sample_ID     Name Group01
3     LH3003     pair1       0
4     LH3004     pair1       1
5     LH3005   pair2       0
6     LH3006   pair2       1
7     LH3007    pair3       0
8     LH3008    pair3       1
9     LH3009 pair4       0
10    LH3010 pair4       1
11    LH3011 pair5       0
12    LH3012 pair5       1
13    LH3013  pair6       0
14    LH3014  pair6       1

Is it possible to do a paired t-test by defining the pairs and the group annotation of the samples based on another dataframe?

Thank you for your help!

回答1:

Here is an lapply method that will store the results of each test in a list. This assumes that each pair is adjacent in the second data.frame,df2 and the first data.frame is named df1.

myTestList <- lapply(seq(1, nrow(df2), 2),  function(i) 
                     t.test(df1[[df2$Sample_ID[i]]], df1[[df2$Sample_ID[i+1]]], paired=TRUE))

which returns

myTestList
[[1]]

    Paired t-test

data:  df1[[df2$Sample_ID[i]]] and df1[[df2$Sample_ID[i + 1]]]
t = -0.50507, df = 5, p-value = 0.635
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
 -0.03453201  0.02319070
sample estimates:
mean of the differences 
           -0.005670653 


[[2]]

    Paired t-test

data:  df1[[df2$Sample_ID[i]]] and df1[[df2$Sample_ID[i + 1]]]
t = -2.5322, df = 5, p-value = 0.05239
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
 -0.0459320947  0.0003458114
sample estimates:
mean of the differences 
            -0.02279314

data

df1 <- read.table(header=TRUE, text="LH3003  LH3004  LH3005   LH3006  LH3007  LH3008  LH3009  LH3010   LH3011
cg18478105 0.02329879 0.08103364 0.01611778 0.01691191 0.01886975 0.01885553 0.01647439 0.02120779 0.01168622
cg14361672 0.09479536 0.07821380 0.02522833 0.06467310 0.05387729 0.05866673 0.08121820 0.10920162 0.04413263
cg01763666 0.03625680 0.04633759 0.04401555 0.08371531 0.09866403 0.17611284 0.07306743 0.12422579 0.11125146
cg02115394 0.10014794 0.09274320 0.08743445 0.08906313 0.09934032 0.18164115 0.06526380 0.08158144 0.08862067
cg13417420 0.01811630 0.02221060 0.01314041 0.01964530 0.02367295 0.01209913 0.01612864 0.01306061 0.04421938
cg26724186 0.32776266 0.31386294 0.24167480 0.29036142 0.24751268 0.26894756 0.20927278 0.28070790 0.33188921")[1:4]

df2 <- read.table(header=TRUE, text="   Sample_ID     Name Group01
3     LH3003     pair1       0
4     LH3004     pair1       1
5     LH3005   pair2       0
6     LH3006   pair2       1")

回答2:

You need to stack your data and define a pair column and then run the t.test, this is for 1 of the 6 tests:

data2 <- data.frame(x = c(data$LH3003, data$LH3004), pair = c(rep(0, nrow(data)), rep(1, nrow(data))))
t.test(x ~ pair, data2)

回答3:

Here's a variation on @Imo's:

lapply(unique(df2$Name), function(x){
  samples <- df2[df2$Name==x,1]
  t.test(df1[,samples[1]], df1[,samples[2]], paired=T)
})

来源：https://stackoverflow.com/questions/40611064/paired-t-test-with-pairs-and-groups-defined-in-another-dataframe

标签

t-test