It is easy enough to extract genomic ranges and associated meta data from a GRanges object.

library(GenomicRanges)

gr1 <- GRanges(
  seqnames = Rle("chr1", 3),
  ranges = IRanges(c(1, 2, 8), end = c(2, 5, 9)),
  score = 1:3)

show(gr1)
## GRanges object with 3 ranges and 1 metadata column:
##       seqnames    ranges strand |     score
##          <Rle> <IRanges>  <Rle> | <integer>
##   [1]     chr1       1-2      * |         1
##   [2]     chr1       2-5      * |         2
##   [3]     chr1       8-9      * |         3
##   -------
##   seqinfo: 1 sequence from an unspecified genome; no seqlengths

ranges(gr1)
## IRanges object with 3 ranges and 0 metadata columns:
##           start       end     width
##       <integer> <integer> <integer>
##   [1]         1         2         2
##   [2]         2         5         4
##   [3]         8         9         2

mcols(gr1)
## DataFrame with 3 rows and 1 column
##       score
##   <integer>
## 1         1
## 2         2
## 3         3

However, I would like to extract the metadata from a GRanges object for each genomic coordinate in the ranges and insert a 0 for uncovered coordinates. One can achieve this by converting the GRanges object to a data.frame and filling in the metadata values.

df1 <- as.data.frame(gr1)

df1.expanded <- data.frame(chr = "chr1", coord = min(df1$start):(max(df1$end)-1), score = 0)

for(n in 1:nrow(df1.expanded)){
  try(df1.expanded$score[n] <- df1$score[df1$start <= df1.expanded$coord[n] & df1$end > df1.expanded$coord[n]], silent = TRUE)
}

df1.expanded
##    chr coord score
## 1 chr1     1     1
## 2 chr1     2     2
## 3 chr1     3     2
## 4 chr1     4     2
## 5 chr1     5     0
## 6 chr1     6     0
## 7 chr1     7     0
## 8 chr1     8     3

Is there an easier and more efficient way to do this? What I want to do in the end is to correlate the metadata of two GRanges objects in specific genome regions. For one of the GRanges objects uncovered genomic ranges should get a metadata score 0. Are there better ways to achieve this than transforming GRanges objects to data.frames and "expanding" them as shown above?

It is not necessary to use data.frame, even taking your general approach. Here is a rough sketch:

gr.expanded <- GRanges("chr1", IRanges(min(start(gr1)):(max(end(gr1))-1), width=1L), score=0L)

for(n in 1:length(gr.expanded)){
  try(gr.expanded$score[n] <- score(gr1)[start(gr1) <= start(gr.expanded)[n] & end(gr1) > start(gr.expanded)[n]], silent = TRUE)
}

I wouldn't recommend doing that, of course, but it's important to realize that GRanges objects behave much like data.frames.

Martin's answer looks good (probably not necessary to call range() though).

Another option is to just use the coverage vector infrastructure:

gp <- GRanges(coverage(gr1, weight="score"))

You might also look into the GPos container in case the correlation will be computed at the base level.

Maybe one way would be to find the unscored ranges

unscored = setdiff(range(gr1), gr1)

and then update and append the ranges

unscored$score = 0
sort(append(gr1, unscored))
## GRanges object with 4 ranges and 1 metadata column:
##       seqnames    ranges strand |     score
##          <Rle> <IRanges>  <Rle> | <numeric>
##   [1]     chr1       1-2      * |         1
##   [2]     chr1       2-5      * |         2
##   [3]     chr1       6-7      * |         0
##   [4]     chr1       8-9      * |         3
##   -------
##   seqinfo: 1 sequence from an unspecified genome; no seqlengths

Note that in your original data position 2 has scores 1 and 2, whereas in your data.frame it has only score 2.

Based on Michael's answer I can achieve my goal with this code:

library(GenomicRanges)

gr1 <- GRanges(
  seqnames = Rle("chr1", 3),
  ranges = IRanges(start = c(1, 2, 8) + 1, end = c(2, 5, 9)),
  score = 1:3)

gr1
# GRanges object with 3 ranges and 1 metadata column:
#     seqnames    ranges strand |     score
#        <Rle> <IRanges>  <Rle> | <integer>
# [1]     chr1         2      * |         1
# [2]     chr1       3-5      * |         2
# [3]     chr1         9      * |         3
# -------
# seqinfo: 1 sequence from an unspecified genome; no seqlengths

gr1.exp <- GRanges(coverage(gr1, weight="score"))

gp1 <- GPos(gr1.exp)

gp1$score <- rep(gr1.exp$score, width(gr1.exp))

gp1
# GPos object with 9 positions and 1 metadata column:
#     seqnames       pos strand |     score
#        <Rle> <integer>  <Rle> | <integer>
# [1]     chr1         1      * |         0
# [2]     chr1         2      * |         1
# [3]     chr1         3      * |         2
# [4]     chr1         4      * |         2
# [5]     chr1         5      * |         2
# [6]     chr1         6      * |         0
# [7]     chr1         7      * |         0
# [8]     chr1         8      * |         0
# [9]     chr1         9      * |         3
# -------
# seqinfo: 1 sequence from an unspecified genome