Hi:

I used IntegerList to hold my data, and I got DataFrame in the list as an output of functions. However, I intend to combine DataFrame objects in very specific way, where firstly I am gonna combine second, third DataFrame in the list but must proceed duplicate removal, after that I am gonna combine it with first DataFrame but here I allow duplicate. I tried to use lapply functions to make this happen, but I got an error. How can I get my desired output more elegantly in function ? Any idea ?

mini example:

dfList <- list(
  DF.1 = DataFrame(hit.1=IntegerList(1,2,3), hit.2=IntegerList(NA,1,2), hit.3=IntegerList(1,1,2)),
  DF.2 = DataFrame(hit.1=IntegerList(2,3,NA), hit.2=IntegerList(1,2,3), hit.3=IntegerList(1,2,4)),
  DF.3 = DataFrame(hit.1=IntegerList(2,3,NA,NA), hit.2=IntegerList(1,2,NA,3), hit.3=IntegerList(1,2,3,4))
)

I intend to combine IntegerList with specific condition such as :

rbind(dfList[[1L]], 
      unique(rbind(dfList[[2L]], dfList[[3L]])))

but doing this way is not elegant for me, I believe there must be way to make this more elegant. How can I make this happen in functional programming more elegantly? How can I make solution more prettier that can be called in function ?Thanks in advance

> sessionInfo()
R version 3.3.1 (2016-06-21)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows >= 8 x64 (build 9200)

locale:
[1] LC_COLLATE=English_United States.1252 
[2] LC_CTYPE=English_United States.1252   
[3] LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C                          
[5] LC_TIME=English_United States.1252    

attached base packages:
[1] parallel  stats4    stats     graphics  grDevices
[6] utils     datasets  methods   base     

other attached packages:
[1] data.table_1.9.6     rtracklayer_1.34.1  
[3] GenomicRanges_1.26.1 GenomeInfoDb_1.10.0 
[5] IRanges_2.8.0        S4Vectors_0.12.0    
[7] BiocGenerics_0.20.0  BiocInstaller_1.24.0

I believe this is the much prettier way to accomplish your task :

rbind(dfList[[1]], 
      unique(do.call("rbind", dfList[2: length(dfList)])))

cheers :)