Dear Dr. Zhu,

I'm trying to use your bioconductor package to perform some analysis, and
I'm running through a problem which I'm very doubtful on dealing with.

I'll try to be very concise here.

I have two data sets (DS1 and DS2) in which I want to run
annotatePeakInBatch against the same AnnotationData (AD).

All of them are already RangedData, so all I need to do is run the function
normaly  annotatePeakInBatch(DS1,AnnotationData=AD)

DS1 has exactly 12.263 entries and running system.time() over the call, it
yielded me this:


user     system  elapsed
126.98   0.13    127.93


That's OK, the function worked flawlessly, the problem arise with the
second dataset (DS2). It's huge, very big. It's a dataset of short reads
with 9.696.611 entries (yeah, almost 10million reads)

I ran it against the same AnnotationData and it's been running for more
than 24 hours right now. The question is... is that normal ?

Should I really expect such a long time to do all the calculations ? Could
you please elucidate something about the complexity of the algorithm being
used ?

I would be very pleased if it's also possible to present me some benchmarks
you'd done when developing the package, this run is just one of many others
that I need to do and it would be great to have some information on how
long it'll last, so I can build my work schedule properly.

The size of the database AD is 86.046 entries, the machine that is running
this is a server with 4 quad-cores and 22GB of RAM which 40% are being used
by R running the function.

Thanks,
Halian

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