I have a wig file that I've read into a granges-like object using a function that I wrote that calls the `rtracklayer` package:

    read_wig <- function(x, format='wig', genome='mm9') {
      suppressMessages(library(rtracklayer))  
      merged_wig <- import.wig(x, format=format, genome=genome)
      merged_wig <- keepSeqlevels(merged_wig, paste0('chr', c(seq(1,19), 'X', 'Y')), pruning.mode="coarse")
      return(merged_wig)
    }

    wig <- read_wig('~/path/to/wig')

The code above returns: 

    > wig
    UCSC track 'MEFES_K27AC.downsampled.sorted'
    UCSCData object with 13274466 ranges and 1 metadata column:
                 seqnames               ranges strand |     score
                    <Rle>            <IRanges>  <Rle> | <numeric>
             [1]     chr1          [  1,  200]      * |         0
             [2]     chr1          [201,  400]      * |         0
             [3]     chr1          [401,  600]      * |         0
             [4]     chr1          [601,  800]      * |         0
             [5]     chr1          [801, 1000]      * |         0
             ...      ...                  ...    ... .       ...
      [13274462]     chrY [15901401, 15901600]      * |         0
      [13274463]     chrY [15901601, 15901800]      * |         0
      [13274464]     chrY [15901801, 15902000]      * |         0
      [13274465]     chrY [15902001, 15902200]      * |         0
      [13274466]     chrY [15902201, 15902400]      * |         0
      -------
      seqinfo: 21 sequences from mm9 genome

Now with this object **I'd like to compute the sum of scores within a window around each range for each row in the object**. For example, I'd like to compute the sum of score between ranges 1-10000 (123 for this example) and add this entry as a column next to score. I'd like to do this for each row. 

   > expected_output
    UCSC track 'MEFES_K27AC.downsampled.sorted'
    UCSCData object with 13274466 ranges and 1 metadata column:
                 seqnames               ranges strand |     score  score_10000
                    <Rle>            <IRanges>  <Rle> | <numeric>    <numeric>
             [1]     chr1          [  1,  200]      * |         0          123
             [2]     chr1          [201,  400]      * |         0          ...
             [3]     chr1          [401,  600]      * |         0          ...
             [4]     chr1          [601,  800]      * |         0          ...
             [5]     chr1          [801, 1000]      * |         0          ...
             ...      ...                  ...    ... .       ...
      [13274462]     chrY [15901401, 15901600]      * |         0          ...
      [13274463]     chrY [15901601, 15901800]      * |         0          ...
      [13274464]     chrY [15901801, 15902000]      * |         0          ...
      [13274465]     chrY [15902001, 15902200]      * |         0          ...
      [13274466]     chrY [15902201, 15902400]      * |         0          ...
      -------
      seqinfo: 21 sequences from mm9 genome

Ideally I'd like to add columns that compute score ranges from 1-10000, 1-20000, 1-30000, etc. up to 100000.

Any help would be much appreciated! 

EDIT: I've added a wig file here that can be used to run the code above.  

One way to do this fast is to take advantage of the fixed width WIG data (200bp). Then it is easy to compute how many neighboring elements to include in the sum.

window <- 10000L
width <- 200L
w <- resize(IRanges(seq_along(wig), width=1L), window/width, fix="center")
w <- restrict(w, 1L, rep(end(seqnames(wig)), width(seqnames(wig))))
ans <- sum(extractList(wig$score, w))

Note that the call to restrict() is going to truncate the windows at the edges. The important thing to realize is that an IRanges object is an IntegerList. Let me know if anything doesn't make sense.