R : How to create objects with a function which name and value depend on an argument, and that these-CodePudding

I have the following situation: I have different dataframes, I would like to be able, for each dataframe, to create 2 dataframes according to the value of one of the columns (log2FoldChange>1 and logFoldChange<-1).

For this I use the following code:

DJ29_T0_Overexpr = DJ29_T0[which(DJ29_T0$log2FoldChange > 1),]
DJ29_T0_Underexpr = DJ29_T0[which(DJ21_T0$log2FoldChange < -1),]

DJ229_T0 being one of my dataframe.

First problem: the sign for the dataframe where log2FoldChange < -1 is not taken into account.

But the main problem is at the time of making the function, I wrote the following:

spliteOverUnder <- function(res){
  nm <-deparse(substitute(res))
  assign(paste(nm,"_Overexpr", sep=""), res[which(as.numeric(as.character(res$log2FoldChange)) > 1),])
  assign(paste(nm,"_Underexpr", sep=""), res[which(as.numeric(as.character(res$log2FoldChange)) < -1),])
}

Which I then ran with :

spliteOverUnder(DJ29_T0)

No error message, but my objects are not exported in my global environment. I tried with return(paste(nm,"_Overexpr", sep="") but it only returns the object name but not the associated dataframe.

Using paste() forces the use of assign(), so I can't do :

spliteOverUnder <- function(res){
  nm <-deparse(substitute(res))
  paste(nm,"_Overexpr", sep="") <<- res[which(as.numeric(as.character(res$log2FoldChange)) > 1),]
  paste(nm,"_Underexpr", sep="") <<- res[which(as.numeric(as.character(res$log2FoldChange)) < -1),]
}

spliteOverUnder(DJ24_T0)

I encounter the following error:

Error in paste(nm, "_Overexpr", sep = "") <<- res[which(as.numeric(as.character(res$log2FoldChange)) > : 
  could not find function "paste<-"

If you've encountered this difficulty before, I'd appreciate a little help. And if you knew, once the function works, how to use a For loop going through a list containing all my dataframes to apply this function to each of them, I'm also a taker.

Thanks

CodePudding user response：

When assigning, use the pos argument to hoist the new objects out of the function.

function(){
    assign(x = ..., value = ...,
           pos = 1 ## see below
    )
}

... where 0 = the function's local environment, 1 = the environment next up (in which the function is defined) etc.

edit A general function to create the split dataframes in your global environment follows. However, you might rather want to save the new dataframes (from within the function) or just forward them to downstream functions than cram your workspace with intermediary objects.

splitOverUnder <- function(the_name_of_the_frame){
    df <- get(the_name_of_the_frame)
    df$cat <- cut(df$log2FoldChange,
                  breaks = c(-Inf, -1, 1, Inf),
                  labels = c('underexpr', 'normal', 'overexpr')
                  )
    split_data <- split(df, df$cat)
    sapply(c('underexpr', 'overexpr'),
           function(n){
               new_df_name <- paste(the_name_of_the_frame, n, sep = '_')
               print(new_df_name)
               assign(x = new_df_name,
                      value = split_data$n,
                      envir = .GlobalEnv
                      )
           }
           )
}

## say, df1 and df2 are your initial dataframes to split:
sapply(c('df1', 'df2'), function(n) splitOverUnder(n))

CodePudding user response：

Thank you very much I_O, my function works very well like this thanks to you :

spliteOverUnder <- function(res){
  nm <-deparse(substitute(res))
  assign(paste(nm,"_Overexpr", sep=""), res[which(as.numeric(as.character(res$log2FoldChange)) > 1),], pos=1)
  assign(paste(nm,"_Underexpr", sep=""), res[which(as.numeric(as.character(res$log2FoldChange)) < -1),], pos=1)
}

spliteOverUnder(DJ29_T0)

Do you know how to do a For loop using a list of dataframes?

For example:

listRes <- list(DJ21_T0, DJ24_T0, DJ29_T0, DJ32_T0,
                DJ24_DJ21, DJ29_DJ21, DJ32_DJ21,
                DJ21_DJ24, DJ29_DJ24, DJ32_DJ24,
                DJ21_DJ29, DJ24_DJ29, DJ32_DJ29,
                DJ21_DJ32, DJ24_DJ32, DJ29_DJ32,
                Rec2_T0, Rec6_T0, Rec9_T0,
                Rec2_DJ32, Rec6_DJ32, Rec9_DJ32,
                Rec6_Rec2, Rec9_Rec2,
                Rec2_Rec6, Rec9_Rec6,
                Rec2_Rec9, Rec6_Rec9)

for(i in listRes){
  spliteOverUnder(i)}

This did not work and created a dataframe i, a dataframe i_Overexpr and a dataframe i_Underexpr....