adding a data to new column if seperated by "+" sign using R

Following previous question,enter link description here I have extra informations with my data,I included the gene with the data. Since same gene were predicted as different enzyme, results were combined as "+" sign, but now I would like to split the results as given her below
My dataframe look like following

df <-data.frame(Gene= c("A", "B", "C","D","E","F"),
                 G1=c("GH13_22+CBM4",  "GH109+PL7+GH9","GT57", "AA3","",""),
                 G2=c("GH13_22","","GT57+GH15","AA3", "GT41","PL+PL2"),
                 G3=c("GH13", "GH1O9","", "CBM34+GH13+CBM48", "GT41","GH16+CBM4+CBM54+CBM32"))

and output if like this one down here

df2<-data.frame(Gene= c("A","A","B", "B","B","C","C","D","D","D","E","F","F","F","F"),
                G1=c("GH13_22","CBM4","GH109","PL7","GH9","GT57","GT57","AA3","AA3","AA3","","","","",""),
                G2=c("GH13_22","GH13_22","","","","GT57","GH15","AA3","AA3","AA3", "GT41","PL","PL2","",""),
            G3=c("GH13","","GH1O9","GH1O9", "GH1O9","","","CBM34","GH13","CBM48", "GT41","GH16","CBM4","CBM54","CBM32"))

Kindly help

It was harder than I thought but here's a way.

The main idea is to use the function str_split_fixed to split string and return a fixed number of separated values, with "" padded if the input is too short. Note: I selected 4 here, but you can choose an upper bound much higher to accommodate for longer strings.

library(stringr)
df[-1] <- lapply(df[-1], \(x) asplit(str_split_fixed(x, "\\+", 4), 1))

#  Gene                G1             G2                       G3
#1    A GH13_22, CBM4, ,   GH13_22, , ,                GH13, , , 
#2    B GH109, PL7, GH9,          , , ,               GH1O9, , , 
#3    C        GT57, , ,  GT57, GH15, ,                    , , , 
#4    D         AA3, , ,       AA3, , ,      CBM34, GH13, CBM48, 
#5    E            , , ,      GT41, , ,                GT41, , , 
#6    F            , , ,     PL, PL2, ,  GH16, CBM4, CBM54, CBM32

This results in a data.frame with G1:G3 as column-matrix, i.e. each element is a matrix of size 1 x 4. Then, the remaining code unnests the matrices to multiple elements in long format, replace empty strings with NAs, remove rows with only NAs, and then fill the remaining values by group:

library(dplyr)
library(tidyr)

unnest_longer(df, col = G1:G3) %>% 
  mutate(across(G1:G3, ~ na_if(.x, ""))) %>% 
  filter(if_any(G1:G3, complete.cases)) %>% 
  group_by(Gene) %>% 
  fill(G1:G3)

   Gene      G1      G2    G3
1     A GH13_22 GH13_22  GH13
2     A    CBM4 GH13_22  GH13
3     B   GH109    <NA> GH1O9
4     B     PL7    <NA> GH1O9
5     B     GH9    <NA> GH1O9
6     C    GT57    GT57  <NA>
7     C    GT57    GH15  <NA>
8     D     AA3     AA3 CBM34
9     D     AA3     AA3  GH13
10    D     AA3     AA3 CBM48
11    E    <NA>    GT41  GT41
12    F    <NA>      PL  GH16
13    F    <NA>     PL2  CBM4
14    F    <NA>     PL2 CBM54
15    F    <NA>     PL2 CBM32

You could also do:

library(dplyr) #version >=1.10
df %>%
   pivot_longer(-Gene)%>%
   filter(nzchar(value)) %>%
   separate_rows(value, sep = '\\+') %>%
   mutate(Id = row_number(), .by = c(Gene, name))%>%
   pivot_wider()

# A tibble: 15 × 5
   Gene     Id G1      G2      G3   
   <chr> <int> <chr>   <chr>   <chr>
 1 A         1 GH13_22 GH13_22 GH13 
 2 A         2 CBM4    NA      NA   
 3 B         1 GH109   NA      GH1O9
 4 B         2 PL7     NA      NA   
 5 B         3 GH9     NA      NA   
 6 C         1 GT57    GT57    NA   
 7 C         2 NA      GH15    NA   
 8 D         1 AA3     AA3     CBM34
 9 D         2 NA      NA      GH13 
10 D         3 NA      NA      CBM48
11 E         1 NA      GT41    GT41 
12 F         1 NA      PL      GH16 
13 F         2 NA      PL2     CBM4 
14 F         3 NA      NA      CBM54
15 F         4 NA      NA      CBM32

You can drop the Id column by using %>%select(-Id)