Hi John, what I don't get - I specify the output format "m:grd", my tool generates multiple output files in dataset_id_files folder, but the dataset_id.dat file is empty. I need to call this regenerate_primary_file() to add the HTML with the file list to the dat file. But I'm not sure where? -Alex -----Original Message----- From: jmchilton@gmail.com [mailto:jmchilton@gmail.com] On Behalf Of John Chilton Sent: Friday, 19 October 2012 6:16 AM To: Khassapov, Alex (CSIRO IM&T, Clayton) Subject: Re: [galaxy-dev] pass more information on a dataset merge On Tue, Oct 16, 2012 at 11:11 PM, <Alex.Khassapov@csiro.au> wrote:
Hi John,
I am definitely interested in this idea, not only me - we are currently working on moving a few scientific tools (not related to genome) into cloud using Galaxy.
Great. My interests in Galaxy are mostly outside of genomics as well, it is good to have more people utilizing Galaxy in this way because it will force the platform to become more generic and address more broader use cases.
We will try it further and see if we need any changes. For now one improvement would be nice, make dataset_id.dat contain list of paths to the location of the uploaded files, so by displaying html page the user could just click on the link and download the file.
Code that attempted to do this was in there, but didn't work obviously. I have now fixed it up. Thanks for beta testing. -John
We are pretty new to Galaxy, so our understanding of Galaxy is pretty limited.
Thanks again,
Alex
-----Original Message----- From: jmchilton@gmail.com [mailto:jmchilton@gmail.com] On Behalf Of John Chilton Sent: Wednesday, 17 October 2012 3:21 AM To: Khassapov, Alex (CSIRO IM&T, Clayton) Subject: Re: [galaxy-dev] pass more information on a dataset merge
Wow, thanks for the rapid feedback! I have made the changes you have suggested. It seems you must be interested in this idea/implementation. Let me know if you have specific use cases/requirements in mind and/or if you would be interested in write access to the repository.
-John
On Mon, Oct 15, 2012 at 11:51 PM, <Alex.Khassapov@csiro.au> wrote:
Hi John,
I tried your galaxy-central-homogeneous-composite-datatypes implementation, works great thank you (and Jorrit).
A couple of fixes:
1. Add multi_upload.xml to too_conf.xml 2. lib/galaxy/tools/parameters/grouping.py line 322 (in get_filenames( context )) - "if ftp_files is not None:" Remove "is not None" as ftp_files is empty [], but not None, then line 331 "user_ftp_dir = os.path.join( trans.app.config.ftp_upload_dir, trans.user.email )" throws an exeption if ftp_upload_dir isn't set.
Alex
-----Original Message----- From: galaxy-dev-bounces@lists.bx.psu.edu [mailto:galaxy-dev-bounces@lists.bx.psu.edu] On Behalf Of John Chilton Sent: Tuesday, 16 October 2012 1:07 AM To: Jorrit Boekel Cc: galaxy-dev@lists.bx.psu.edu Subject: Re: [galaxy-dev] pass more information on a dataset merge
Here is an implementation of the implicit multi-file composite datatypes piece of that idea. I think the implicit parallelism may be harder.
https://bitbucket.org/galaxyp/galaxy-central-homogeneous-composite-da t atypes/compare
Jorrit do you have any objection to me trying to get this included in galaxy-central (this is 95% code I stole from you)? I made the changes against a clean galaxy-central fork and included nothing proteomics specific in anticipation of trying to do that. I have talked with Jim Johnson about the idea and he believes it would be useful his mothur metagenomics tools, so the idea is valuable outside of proteomics.
Galaxy team, would you be okay with including this and if so is there anything you would like to see either at a high level or at the level of the actual implementation.
-John
------------------------------------------------ John Chilton Senior Software Developer University of Minnesota Supercomputing Institute Office: 612-625-0917 Cell: 612-226-9223 Bitbucket: https://bitbucket.org/jmchilton Github: https://github.com/jmchilton Web: http://jmchilton.net
On Mon, Oct 8, 2012 at 9:24 AM, John Chilton <chilton@msi.umn.edu> wrote:
Jim Johnson and I have been discussing that approach to handling fractionated proteomics samples as well (composite datatypes, not the specifics of the interface for parallelizing).
My perspective has been that Galaxy should be augmented with better native mechanisms for grouping objects in histories, operating over those groups, building workflows that involve arbitrary numbers of inputs, etc... Composite data types are kindof a kludge, I think they are more useful for grouping HTML files together when you don't care about operating on the constituent parts you just want to view pages a as a report or something. With this proteomic data we are working with, the individual pieces are really interesting right? You want to operate on the individual pieces with the full array of tools (not just these special tools that have the logic for dealing with the composite datatypes), you want to visualize the files, etc... Putting these component pieces in the composite data type extra_files path really limits what you can do with the pieces in Galaxy.
I have a vague idea of something that I think could bridge some of the gaps between the approaches (though I have no clue on the feasibility). Looking through your implementation on bitbucket it looks like you are defining your core datatypes (MS2, CruxSequest) as subclasses of this composite data type (CompositeMultifile). My recommendation would be to try to define plain datatypes for these core datatype (MS2, CruxSequest) and then have the separate composite datatype sort of delegate to the plain datatypes.
You could then continue to explicitly declare subclasses of the composite datatype (maybe MS2Set, CruxSequestSet), but also maybe augement the tool xml so you can do implicit data type instances the way you can with tabular data for instance (instead of defining columns you would define the datatype to delegate to).
The next step would be to make the parallelism implicit (i.e pull it out of the tool wrapper). Your tool wrappers wouldn't reference the composite datatypes, they would reference the simple datatypes, but you could add a little icon next to any input that let you replace a single input with a composite input for that type. It would be kind of like the run workflow page where you can replace an input with a multiple inputs. If a composite input (or inputs) are selected the tool would then produce composite outputs.
For the steps that actually combine multiple inputs, I think in your case this is perculator maybe (a tool like interprophet or Scaffold that merges peptide probabilities across runs and groups proteins), then you could have the same sort of implicit replacement but instead of for single inputs it could do that for multi-inputs (assuming the Galaxy powers that be accept my fixes for multi-input tool parameters: https://bitbucket.org/galaxy/galaxy-central/pull-request/76/multi-input-data...).
The upshot of all of that would be that then even if these composites datatypes aren't used widely, other people could still use your proteomics tools (my users are definitely interested in Crux for instance) and you could then use other developers' proteomic tools with your composite datatypes even though they weren't designed with that use case in mind (I have msconvert, myrimatch, idpicker, proteinpilot, Ira Cooke has X! Tandem, OMSSA, TPP, and NBIC has an entire suite of label free quant tools). A third benefit would be that people working in other -omicses could make use of the homogenous composite datatype implementation without needing to rewrite their wrappers and datatypes.
There is probably something that I am missing that makes this very difficult, let me know if you think this is a good idea and what its feasibility might be. I forked your repo and set off to try to implement some of this stuff last week and I ended up with my galaxy pull requests to improve batching workflows and multi-input tool parameters instead, but I hope to eventually get around to it.
-John
------------------------------------------------ John Chilton Senior Software Developer University of Minnesota Supercomputing Institute Office: 612-625-0917 Cell: 612-226-9223 Bitbucket: https://bitbucket.org/jmchilton Github: https://github.com/jmchilton Web: http://jmchilton.net
On Mon, Oct 1, 2012 at 8:24 AM, Jorrit Boekel <jorrit.boekel@scilifelab.se> wrote:
Dear list,
I thought I was working with fairly large datasets, but they have recently started to include ~2Gb files in sets of >50. I have ran these sort of things before as merged data by using tar to roll them up in one set, but when dealing with >100Gb tarfiles, Galaxy on EC2 seems to get very slow, although that's probably because of my implementation of dataset type detection (untar and read through files).
Since tarring/untarring isn't very clean, I want to switch from tarring to creating composite files on merge by putting a tool's results into the dataset.extra_files_path. This doesn't seem to be supported yet, because we currently pass in do_merge the output dataset.filename to the respective datatype's merge method.
I would like to pass more data to the merge method (let's say the whole dataset object) to be able to get the composite files directory and 'merge' the files in there. Good idea, bad idea? If anyone has views on this, I'd love to hear them.
cheers, jorrit
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