Hi Jose,

Very glad to know that you have this working.

You question is difficult to address with specificity, as these are completely different algorithms. But in general, any alignment algorithm (Bowtie included) has some sort of indexing strategy (some are better than others) to minimize what is held in memory and process bulk data through. See the Bowtie documentation for how this is achieved.

The interval operations tools also have an indexing strategy, specifically, the second input file is the portion loaded memory and the first file is processed against it. So, if you want use an extremely large dataset (or just want to the job to run quicker) try to use it as the first input file if possible.

These tools are designed to be used together and with other tools to create workflows, so there should pretty much always be some way to break jobs up (as you did) to get them through the tools, on even modest systems: http://wiki.g2.bx.psu.edu/Learn/Interval%20Operations

Take care,

Jen Galaxy team

On 5/7/12 8:30 AM, Xianrong Wong wrote:

Hello Jennifer, thanks for the advise. It worked when I did it a chromosome at a time. Is there a reason why this is so much more computationally heavy as compared to bowtie? (mapping 190 million reads took only 3-4 hours for me) Jose

On Fri, May 4, 2012 at 7:55 PM, Jennifer Jackson <jen@bx.psu.edu mailto:jen@bx.psu.edu> wrote:

Hello Jose,

It sounds as if the job is running out of memory. Since you are
already working on a cloud, I am going to make the assumption that
you have explored the server options with high-capacity memory
there. But if not, that is one place to start, in particular your
EC2 Instance type, as described on this wiki:
http://wiki.g2.bx.psu.edu/__Admin/Cloud/CapacityPlanning
<http://wiki.g2.bx.psu.edu/Admin/Cloud/CapacityPlanning>

However, even if that was an option, you may want to consider
running your in data through in another way - by running smaller
jobs, then merging results, to avoid the large jobs. For example, in
the last step where you join to the "full BamHI delimited bin file",
instead join to groups of bins in that file (perhaps grouped by
chromosome), then combine the results to produce the full output.

Hopefully this helps provide some options,

Jen
Galaxy team


On 5/4/12 2:18 PM, Xianrong Wong wrote:

    Hello,
             I have binned the mouse genome into fragments based on
    restriction enzyme cut sites.  So each bin is a fragment flanked
    by say
    BamHI.  The output file is in the interval format: chr# start
    and end
    coordinates of each bin.  I want to count how many times each
    bin has
    reads that align to it.  I mapped my reads using bowtie and
    generated a
    dataset (interval format) for the aligned reads.  I then used
    join in
    "operate on genomic intervals" and asked it to return intervals that
    innerjoin the "bin file".  The subsequent steps involve grouping and
    counting and then joining back to the 1st dataset (BamHI delimited
    bins).  I have tried this workflow on small datasets and it worked.
    However when I subject my full alignment file and full BamHI
    delimited
    bin file, the tool fails.  I am doing this on cloud.  Any advice
    would
    be appreciated!

    Jose


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