I have a question similar to this one, but my dataset is a bit bigger: 50 columns with 1 column as UID and other columns carrying either TRUE or NA
With dplyr you could also do
df %>% mutate_each(funs(replace(., is.na(.), F)), x1, x2)
It is a bit less readable compared to just using replace() but more generic as it allows to select the columns to be transformed. This solution especially applies if you want to keep NAs in some columns but want to get rid of NAs in others.