Concatenate strings by group with dplyr for multiple columns [duplicate]

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This question already has an answer here:

• Collapse all columns by an ID column [duplicate] 5 answers

Hi I need to concatenate strings by groups for multiple columns. I realise that versions of this question has been asked several times (see Aggregating by unique identifier and concatenating related values into a string), but they usually involve concatenating values of a single column.

My dataset is something like:

Sample  group   Gene1   Gene2   Gene3
A       1       a       NA      NA
A       2       b       NA      NA
B       1       NA      c       NA
C       1       a       NA      d
C       2       b       NA      e
C       3       c       NA      NA

I want to get it into a format where each samples takes only 1 row (the group column is optional):

Sample  group   Gene1   Gene2   Gene3
A       1,2     a,b     NA      NA
B       1       NA      c       NA
C       1,2,3   a,b,c   NA      d,e

Since the number of genes can go up to the thousands, I can't simply specify the columns that I wish to concatenate. I know aggregate or dplyr can be used to get the groups but I can't figure out how to do it for multiple columns.

Thanks in advance!

Edit

As my dataset is very large containing thousands of genes, I realised dplyr is too slow. I've been experimenting with data.table and the following code can also get what I want:

setDT(df)[, lapply(.SD, function(x) paste(na.omit(x), collapse = ",")), by = Sample]

The output is now:

   Sample group Gene1 Gene2 Gene3
1:      A   1,2   a,b            
2:      B     1           c      
3:      C 1,2,3 a,b,c         d,e

Thanks for all your help!

Answer 1

For these purposes, there are the summarise_all, summarise_at, and summarise_if functions. Using summarise_all:

df %>%
  group_by(Sample) %>%
  summarise_all(funs(paste(na.omit(.), collapse = ",")))

# A tibble: 3 × 5
  Sample group Gene1 Gene2 Gene3
   <chr> <chr> <chr> <chr> <chr>
1      A   1,2   a,b            
2      B     1           c      
3      C 1,2,3 a,b,c         d,e

Answer 2

using dplyr, you can try:

dft %>%
  group_by(Sample) %>%
  summarise_each(funs( toString(unique(.))))

which gives:

# A tibble: 3 × 5
  Sample   group   Gene1 Gene2    Gene3
   <chr>   <chr>   <chr> <chr>    <chr>
1      A    1, 2    a, b    NA       NA
2      B       1      NA     c       NA
3      C 1, 2, 3 a, b, c    NA d, e, NA

Edit: @Axeman had the right idea with using na.omit(.) to get rid of null values