I am maintaining a (still young) suite of command line tools (written
Python) for identification of mutations in model organism genomes
through whole-genome sequencing (https://sourceforge.net/projects/mimodd/
MiModD aims at geneticists that do not have much background in
bioinformatics, and it's supposed to make WGS analysis for small model
organism genomes (anything from yeast to fish) possible on regular PCs,
so it's not a cloud/cluster solution.
We do support Galaxy though through a complete set of tool wrappers for
- to provide a graphical user interface
- to offer labs the possibility to install the software on one dedicated
machine, but run analyses from any machine (typically with Windows
- to keep analysis workflows documented and reproducible.
Currently, we advise users to take advantage of these features and
install a local instance of Galaxy even though it will be running then
only on a single desktop PC (or even just a notebook). After
installation of Galaxy our software simply copies its wrapper xmls over
to the tools folder and modifies the tool_conf file to integrate itself.
In addition, users have to install a bit of other third-party software
(samtools, snap aligner, optionally snpeff) that our code relies on.
[End of lengthy introduction]
So my question is: in what way could the package profit from being
uploaded to a Galaxy toolshed ? I guess it would mean quite some extra
work from my side since I'm not familiar with the whole procedure, so
are there benefits (visibility, ease of installation, etc.) that are
worth the effort ?
Yes, it would mean extra work for you, but it is worth the effort.
One main reason, you already mentioned, visibility. If done right and
you are supporting your wrapper these will probably be used by many
different Galaxy Servers out there. Just have a look at a few tools that
are from the same field as your tools and look at the download counter.
Easy installation is also one reason, as soon as you have a Galaxy
server it can be trivial to install your tools, suppose you define all
dependencies. -> But defining dependencies is easy nowadays, and even
better, many dependencies are already available in the Tool Shed. If you
depend on numpy, insert a few lines to point to the correct numpy
dependency and you are done.
We can help you if you encounter any problems in that step, or just drop
by during the GCC developer workshop. We will give a hands-on how to
wrap your tools.
Reproducibility: With the Tool Shed you get reproducibility for free.
You can install many different version of your tools and Galaxy will
take care to select the correct one to reproduce your results.
You can also share your workflows in the Tool Shed. Convince others from
your tools, export your workflows and and anyone can test it with a few
Be part of a very nice community, which tries hard to make bioinformatic
(and more) tools accessible for everyone.
Thanks a real lot for any feedback,
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