We have a GRanges object with motifs of interest:

>motifs_gr
GRanges object with 78181 ranges and 1 metadata column:
          seqnames              ranges strand |    regionID
             <Rle>           <IRanges>  <Rle> | <character>
      [1]     chr1       829075-829135      + |       donor
      [2]     chr1       847777-847837      + |       donor
      [3]     chr1       849573-849633      + |       donor
      [4]     chr1       852081-852141      + |       donor
      [5]     chr1       852737-852797      + |       donor
      ...      ...                 ...    ... .         ...
  [78177]     chrX 155334340-155334400      - |       donor
  [78178]     chrX 155513955-155514015      - |       donor
  [78179]     chrX 155524425-155524485      - |       donor
  [78180]     chrX 155545065-155545125      - |       donor
  [78181]     chrX 155612761-155612821      - |       donor
  -------
  seqinfo: 23 sequences from an unspecified genome; no seqlengths

We import the scores from BigWigFile like this:

gr_frq_mtx = import.bw(snakemake@input[['g1000SNPTrack']], which = motifs_gr, 
                          as = 'NumericList')%>%as.matrix

It turns out that the indexes of the resulting matrix do not match those of original GRanges objects (i.e., n-th row of the matrix does not necessarilly represent the n-th motif in GRanges). For us it is very important though. How could one overcome that?

Thanks in advance,

Stefan.

This could be improved, but as it is, there are two options:

1. Ensure that the GRanges is sorted by the seqlevels as they are in the BigWig file.
2. The resulting NumericList contains a metadata() field named "ranges", which is the which ranges in the order of the result.