Cool, I got a tweet about this tool from @GalaxyProject[1].

To further explain what I'm trying to accomplish here, as I realized
not everybody might know what using "Multiple Output Files" and
specifically "Number of Output datasets cannot be determined until
tool run"[2] entails.

The current Barcode Splitter available on Galaxy Main and based on
FASTX-toolkit by Assaf Gordon, makes all output files accessible
through HTML links. This is not very convenient, as if you want to
use, and you probably do, these outputs in a downstream analysis
inside Galaxy, your only solution right now is to download the linked
files in the HTML output and manually re-import then into Galaxy. The
tool I wrote includes the option of writing the output files(splitted
FASTA or FASTQ files) with a naming convention that can be used with
Galaxy's "Multiple Output Files" so all results files are
automatically added to your history. I believe you still can't easily
use this tool upstream in a workflow. As I far as I can tell tools
without a known number of outputs can't be used upstream in workflows.
I do think you can accomplish some automation using the API, although
I haven't tested this yet.

[1]https://twitter.com/galaxyproject/status/377497531745595392
[2]http://wiki.galaxyproject.org/Admin/Tools/Multiple%20Output%20Files#Number_of_Output_datasets_cannot_be_determined_until_tool_run

Best,
Carlos

On Fri, Sep 6, 2013 at 1:58 PM, Carlos Borroto <carlos.borr...@gmail.com> wrote:
> Hi,
>
> I was wondering if I could get someone to test this new barcode
> splitter I wrote. The main reason for me to duplicate the already
> great fastx-toolkit based splitter, is so I can use galaxy's multiple
> output capabilities.
>
> You can find this tool in the testtoolshed for now(after some more
> testing I will moved to the main toolshed):
> http://testtoolshed.g2.bx.psu.edu/view/cjav/split_by_barcode
>
> Hopefully I got Galaxy's tool dependency system right(it works on my
> box, not that this says much) and installing this tool should be quite
> easy.
>
> I have to say big thanks to Biopython and this[1] anonymous soul for
> making it quite easy to write the actual code doing the heavy lifting.
>
> [1]https://gist.github.com/dgrtwo/3725741
>
> Cheers,
> Carlos
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