Hi Herve,
thanks a lot for re-enabling the subsetting functionality for CompressedRleList
with List-like objects.
While things work now, I noticed a big difference in execution time for the
following operations:
with IRanges_1.18.2
rles <- RleList(Rle(values=TRUE,lengths=10000),
Rle(values=TRUE,lengths= 10000),
Rle(values=TRUE,lengths= 10000),
Rle(values=TRUE,lengths=10000),
Rle(values=TRUE,lengths=10000),
Rle(values=TRUE,lengths=10000),
Rle(values=TRUE,lengths=10000),
Rle(values=TRUE,lengths=10000),
compress=TRUE)
system.time(seqselect( rles, unname(list(a=20:108, b=41:131, c=21:105,
d=1:1234,
e=4:5, f=1223:1243, g=432:5234, h=444:5555) )) <- TRUE)
clocks ca. *0.040s *on my system.
R 3.0.2 with other attached packages:
[1] Rsamtools_1.12.2 Biostrings_2.28.0 devtools_1.3
[4] GenomicRanges_1.12.4 IRanges_1.18.2 BiocGenerics_0.6.0
[7] Defaults_1.1-1 BiocInstaller_1.10.3 roxygen2_2.2.2
[10] digest_0.6.3
with IRanges_1.20.5, the same operation is much slower:
system.time( rles[ unname( list(a=20:108, b=41:131, c=21:105, d=1:1234,
e=4:5, f=1223:1243, g=432:5234, h=444:5555)) ] <- TRUE )
takes about *0.45s * more than 10x longer.
R3.0.0 with other attached packages:
[1] devtools_1.3 rtracklayer_1.22.0 Rsamtools_1.14.1
[4] Biostrings_2.30.0 GenomicRanges_1.14.3 XVector_0.2.0
[7] IRanges_1.20.5 BiocGenerics_0.8.0 Defaults_1.1-1
[10] BiocInstaller_1.12.0 roxygen2_2.2.2 digest_0.6.3
I noticed even larger speed degradation with real-life, longer datasets, so
the decrease appears to be non-linear.
Can you reproduce this difference in performance ?
If so, would it be possible to reinstate the old seqselect method for the
sake of efficiency ?
Thomas
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