如何对R中的每一行执行操作（apply（）？）

Question

So I have the following table:

118.00  12.00   25.00   161.00  26.00   2.00    9.00    47.00
76.00   218.00  1.00    21.00   11.00   64.00   0.00    9.00
53.00   124.00  2.00    51.00   86.00   25.00   25.00   0.00    20.00   14.00
212.00  104.00  38.00   46.00

I parse it in the following way:

data2 <- read.table('to_r.txt', fill=T)

I then want to do something with each row. More specifically convert it to contingency table(2xN matrix) and perform the exact Fisher test. I have no problem extracting one row manually and do what I want.

myrow = na.omit(as.numeric(as.vector(data2[4,])))
fisher.test(matrix(myrow, nrow = 2, byrow=TRUE))

But I wanted to ask how to iterate over rows of the table? So function would output statics for each row. I've tried apply() function, but it did not work for me.

Answer 1

You could use apply to generate a list of the Fisher test results:

tests <- apply(data2, 1, function(x) fisher.test(matrix(na.omit(x), nrow=2, byrow=TRUE)))

Then you could access row-specific tests with standard list indexing

tests[[4]]
#   Fisher's Exact Test for Count Data
# 
# data:  matrix(na.omit(x), nrow = 2, byrow = TRUE)
# p-value = 0.0003517
# alternative hypothesis: true odds ratio is not equal to 1
# 95 percent confidence interval:
#  1.467850 4.151196
# sample estimates:
# odds ratio 
#   2.461669 

If you wanted a vector of p-values for each row instead, you could try:

apply(data2, 1, function(x) fisher.test(matrix(na.omit(x), nrow=2, byrow=TRUE))$p.value)
# [1] 0.5809118696 0.0803221157 0.0113166667 0.0003516986