R replacing words in column by annotation dataframe

Question

I have a dataframe with in 1 column gene IDs (data1). In another dataframe I have the corresponding gene names (data2). Data1 also contains cells with multiple genenames, separated with ':', and also a lot of NAs. Preferably I want to add a column to data1 with the corresponding gene names, also separated by ':' if there are multiple. An alternative would be to replace all the genenames in data1 with the corresponding gene names. Any idea how to go about this? Thanks!

a <- c("ENSG00000150401:ENSG00000150403", "ENSG00000185294", "NA")
data1 <- data.frame(a)


b <- c("ENSG00000150401", "ENSG00000150403", "ENSG00000185294")
c <- c("GeneA", "GeneB", "GeneC")
data2 <- data.frame(b,c)

Answer 1

One option involving stringr could be:

data1$res <- str_replace_all(data1$a, setNames(data2$c, data2$b))

                                a         res
1 ENSG00000150401:ENSG00000150403 GeneA:GeneB
2                 ENSG00000185294       GeneC
3                              NA          NA

Answer 2

We can get data1 in long format, left_join data2 and paste values together.

library(dplyr)

data1 %>%
  mutate(row = row_number()) %>%
  tidyr::separate_rows(a, sep = ":") %>%
  left_join(data2, by = c('a' = 'b')) %>%
  group_by(row) %>%
  summarise(a = paste0(a, collapse = ":"), 
            c = paste0(c, collapse = ":")) %>%
  select(-row)

#  a                               c          
#  <chr>                           <chr>      
#1 ENSG00000150401:ENSG00000150403 GeneA:GeneB
#2 ENSG00000185294                 GeneC      
#3 NA                              NA         

Answer 3

Here is another option with gsubfn

library(gsubfn)
data1$res <- gsubfn("\\w+", setNames(as.list(as.character(data2$c)), 
             data2$b), as.character(data1$a))
data1
#                                a         res
#1 ENSG00000150401:ENSG00000150403 GeneA:GeneB
#2                 ENSG00000185294       GeneC
#3                              NA          NA

---

In base R , this can be also done by splitting the 'a' column with strsplit and then do match with a named vector created from 'b', 'c' columns of second dataset

is.na(data1$a) <- data1$a == "NA" # converting to real NA instead of character
i1 <- !is.na(data1$a)
# create named vector
v1 <- setNames(as.character(data2$c), data2$b)
data1$res[i1] <- sapply(strsplit(as.character(data1$a[i1]), ":"), 
           function(x) paste(v1[x], collapse=":"))