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[英]r: Fill two dataframe columns with the t-statistic and p-value from t.test
[英]R, extracting p-value for each row from t.test
我正在尝试对每一行进行 t.test,然后提取 p 值进行绘图。 作为参考,我发现了这篇旧帖子: 从 R 中的 t 检验输出 p 值
这是我的片段:
> pVal143<-apply(mRNA143.data, 1, t.test)$p.value
但是当我尝试调用它时,我只返回“NULL”? 下面是我的几行数据,仅供参考,谢谢。
c.mRNA h.mRNA
1 8.224342 8.520142
2 9.096665 11.762597
3 10.698863 10.815275
4 10.666233 10.972130
5 12.043525 12.140297
使用原始数据集“c007”更新(我需要比较来自“C”值和 H 值的 p 值)。
C1 C2 C3 C4 C5 C6 H1 H2 H3 H4 H5 H6
NP_000005 P01023 Protein Name 8.57345 8.45938 8.68941 8.35913 8.48177 8.44560 8.40986 8.59392 8.46562 8.07999 8.22759 8.41817
NP_000010 P24752 Protein Name 8.32595 8.19273 8.10708 8.48156 7.99014 8.24859 8.78216 8.59592 8.48299 8.52647 8.34797 8.38534
一种解决方案,您必须手动指定哪些列属于每个组以进行比较:
# example data
df = read.table(text = "
C1 C2 C3 C4 C5 C6 H1 H2 H3 H4 H5 H6
8.57345 8.45938 8.68941 8.35913 8.48177 8.44560 8.40986 8.59392 8.46562 8.07999 8.22759 8.41817
8.32595 8.19273 8.10708 8.48156 7.99014 8.24859 8.78216 8.59592 8.48299 8.52647 8.34797 8.38534
", header=T)
library(tidyverse)
df %>%
rowwise() %>%
mutate(pval = t.test(c(C1,C2,C3,C4,C5,C6),
c(H1,H2,H3,H4,H5,H6))$p.value) %>%
ungroup()
# # A tibble: 2 x 13
# C1 C2 C3 C4 C5 C6 H1 H2 H3 H4 H5 H6 pval
# <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
# 1 8.57 8.46 8.69 8.36 8.48 8.45 8.41 8.59 8.47 8.08 8.23 8.42 0.161
# 2 8.33 8.19 8.11 8.48 7.99 8.25 8.78 8.60 8.48 8.53 8.35 8.39 0.0110
一种替代解决方案,您可以在其中重塑数据并从每列的第一个字母创建 2 个组:
df %>%
mutate(id = row_number()) %>% # add row id
gather(key, value, -id) %>% # reshape dataset
mutate(key = substr(key,1,1)) %>% # create a group column from first letter (will be used for the t.test comparison)
group_by(id) %>% # for each row
summarise(pval = t.test(value ~ key)$p.value) # get p value
# # A tibble: 2 x 2
# id pval
# <int> <dbl>
# 1 1 0.161
# 2 2 0.0110
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