@EconomiCurtis gave you a great solution.
You can transform your data into a data frame or a tibble (here I will use a tibble):
library(tidyverse)
dat <- tibble(
a = c(22, 26),
b = c(96, 55),
c = c(55, 10),
d = c(66, 10)
)
Then you can use @EconomiCurtis's solution with the function rowSums:
rowSums(dat)[1] / rowSums(dat)[2]
or you can sum across rows directly yourself:
sum(dat[1, ]) / sum(dat[2, ])
Either solution will give the result (in this example: 2.366337).