Hi. Interesting discussion!

On Feb 19, 12:12 pm, Istvan Albert <[email protected]> wrote:
> On Feb 18, 2:25 pm, James Taylor <[email protected]> wrote:
>
> > As requested, I've put together an example of using the different  
> > intersection algorithms in bx, with some rough timings.
>
> Nice. I'll see how it compares to other approaches. Also maybe you've
> just created the quintessetial dataset and timing that will be used to
> compare all interval querying from now on....
>
> On a related note I've read an interesting blog post today on using
> python for interval query.
>
> http://www.logarithmic.net/pfh/blog/01234937824
>

I've since come up with what I consider a better approach. Fast enough
for my needs and easy to implement in an SQL database.

http://www.logarithmic.net/pfh/blog/01235197474

At Istvan's prompting, I've tested this with James' test data set. I
assumed pythonic intervals, ie lower<=x<upper. For
the small-to-big test it doesn't do too badly. There's probably some
room for optimization by converting from Python to C code.

http://www.logarithmic.net/pfh-files/blog/01235197474/pfh_example.py

Timing results on my server:

Query intervals:  hg18_chr1_phastConsElements44wayPlacental.bed.bz2
Target intervals: hg18_chr1_knownGene.bed.bz2
---> Using pfh's method, pure python version
Building: 0.020 seconds
Using: 26.290 seconds
---> Using pfh's method, SQLite version
Building: 0.130 seconds
Using: 38.550 seconds


Query intervals:  hg18_chr1_knownGene.bed.bz2
Target intervals: hg18_chr1_phastConsElements44wayPlacental.bed.bz2
---> Using pfh's method, pure python version
Building: 2.060 seconds
Using: 0.850 seconds
---> Using pfh's method, SQLite version
Building: 6.890 seconds
Using: 2.840 seconds


cheers,
Paul Harrison / VBC / Monash University

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