如何在数据帧的每一列中应用功能?

时间:2019-03-24 02:50:04

标签: r

我在R中有345行和237列的以下数据框:

snp1 snp2 snp3 ... snp237 
0 1 2 ... 0
0 1 1 ... 1
1 1 2 ... 2
1 0 0 ... 0
... ... ... ...
2 2 1 ... 0

我想在每列中应用以下功能:

D=(number of 0)/(number of rows)
H=(number of 1)/(number of rows)
R=(number of 2)/(number of rows)
p=D+(0.5*H)
q=R+(0.5*H)

最后,我想将每个snp的“ p”和“ q”存储在向量中。该函数在R的单个命令中为每个snp计算“ p”和“ q”。可能吗?

输出为:

snp1 snp2 snp3 ... snp237
p1 p2 p3 ... ... p237
q1 q2 q3 ... ... q237

谢谢。

2 个答案:

答案 0 :(得分:1)

#DATA
set.seed(42)
d = data.frame(snp1 = sample(0:2, 10, TRUE),
               snp2 = sample(0:2, 10, TRUE),
               snp3 = sample(0:2, 10, TRUE))

#Function    
foo = function(x){
    len = length(x)
    D = sum(x == 0)/len
    H = sum(x == 1)/len
    R = sum(x == 2)/len
    p = D + 0.5 * H
    q = R + 0.5 * H
    return(c(p = p, q = q))
}

#Run foo for each column   
sapply(d, foo)
#  snp1 snp2 snp3
#p 0.35 0.4  0.35
#q 0.65 0.6  0.65

答案 1 :(得分:1)

这里是tidyverse的一个选项。根据OP的代码中的逻辑创建函数(f1),以返回长度为2的list,然后在summarise_all中使用该函数将函数应用于数据集的每一列< / p>

library(dplyr)
library(tidyr)
f1 <- function(x) {
              H <- 0.5 * mean(x == 1)
              list(list(p = mean(x == 0) + H,
                  q = mean(x == 2) + H))
                  }
df1 %>%
   summarise_all(f1) %>% 
   unnest
#  snp1  snp2  snp3
#1 0.75 0.625 0.375
#2 0.25 0.375 0.625

数据

df1 <- structure(list(snp1 = c(0L, 0L, 1L, 1L), snp2 = c(1L, 1L, 1L, 
 0L), snp3 = c(2L, 1L, 2L, 0L)), class = "data.frame", row.names = c(NA, 
  -4L))