在R中的多个列上展开循环

Question

I have a table (mydf) as shown below. I would like to use this for loop (my code) in R which works for only one column (for ALT1 column in this instance) to loop over all the columns containing ALT1 through ALTn and store the output in separate variables from final1 through finaln. The purpose here is to loop over ALT1 through ALTn to match the nucleotide columns (A,C,G,T,N) and get the corresponding values as shown in the result below.Thank you for your help!

mycode

      final1 <- {}
i <- 1
result =merge(coverage.bam, rows.concat.alt, by="start")

for(i in 1:nrow(result)){
  final1[i] = paste(paste(result$chr[i], result$start[i], result$end[i],sep=":"),"-", 
                   result$REF[i],"(",result[,(as.character(result$REF[i]))][i],")",",", result$ALT1[i],
                   "(",result[,(as.character(result$ALT1[i]))][i][!is.na(result[,(as.character(result$ALT1[i]))][i])],")",sep="")

}

final1

I have tried to expand this code for ALT through ALTn, but it does not work, could you help me solve this please?

final <- list()
setValue<-function(element){
  print(element)
  for(i in 1:nrow(result)){
    final[[i]] = paste(paste(result$chr[i], result$start[i], result$end[i],sep=":"),"-", 
                     result$REF[i],"(",result[,(as.character(result$REF[i]))][i],")",",", result[,element][i],
                     "(",result[,(as.character(result[,element][i])))][i][!is.na(result[,(as.character(result[,element][i])][i])],")",sep="")

  }
}
for(i in colnames(result)){
  if(grepl('ALT', i)){
   setValue(i) 
  }
}

mydf

    chr     start       end  A  C  G  T  N  =  - REF ALT ALT1 ALT2 ALT3 ALTn          
1 chr10 102022031 102022031 NA 34 NA NA NA NA NA   C   G    G NA NA NA       
2 chr10 102220574 102220574  2 22  2  3 NA NA NA   C AGT    A    G    T NA       
3 chr10 115322228 115322228 NA 25 NA NA NA NA NA   C   A    A NA NA NA       
4 chr10 122222925 122222925 30 NA NA NA NA NA NA   A   C    C NA NA NA 
5 chr10 121111042 121111042 NA 48 NA NA NA NA NA   C   T    T NA NA NA 
6 chr10 124444484 124444484 NA 60 NA NA NA NA NA   C   T    T NA NA NA 

Result

"chr10:102022031:102022031-C(34),G()"            "chr10:102220574:102220574-C(22),A(2),G(2),T(3)" "chr10:115322228:115322228-C(25),A()"           
      [4] "chr10:122222925:122222925-A(30),C()"            "chr10:121111042:121111042-C(48),T()"            "chr10:124444484:124444484-C(60),T()"

Answer 1

Try

 p1 <- do.call(paste,c(mydf[1:3], sep=":"))
 p2 <- apply(mydf[c(4:8, 11:16)], 1, function(x) {
            Un1 <- unique(match( x[7:11], names(x)[1:4], nomatch=0))
            i1 <- match(x[6], names(x))
            v1 <- paste0(names(x[i1]),'(', x[i1], ')')
            v2 <- as.numeric(x[Un1])
            v2[is.na(v2)] <- ''
            v3 <-paste(names(x[Un1]), '(', v2, ')', sep='', collapse=",")
            paste(v1, v3, sep=",") })

 paste(p1, p2, sep="-")
 #[1] "chr10:102022031:102022031-C(34),G()"           
 #[2] "chr10:102220574:102220574-C(22),A(2),G(2),T(3)"
 #[3] "chr10:115322228:115322228-C(25),A()"           
 #[4] "chr10:122222925:122222925-A(30),C()"           
 #[5] "chr10:121111042:121111042-C(48),T()"           
 #[6] "chr10:124444484:124444484-C(60),T()"