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Just FYI, I found multiple spelling errors in the documentation and readme.

specically -> specifically

Therefor -> therefore

Instanciating -> Instantiating

aned -> and

Also the first sentence in the readme isn't grammatically correct. This is a cool library, but I think it's important to have these sorts of things cleaned up :)

contribute a pull request?
Many thanks to the persons who submitted pull requests.
Damn, that's a really cool logo they came up with. Looks to me like combining the snake from the Rod of Asclepius, plus Python, plus the DNA double helix and the mouse snake head (which I'm guessing is supposed to stand represent using computers for medicine). Whoever made it, that's pretty awesome.

Oh yeah, the actual package is pretty cool too ;)

It's times like these that I wish I had a better understanding of biology/chemistry/genetics. I fancy myself a Python/data person, does anyone have any advice on what to read to begin understanding how to utilize a package like this?
Apologies for a trivial objection: but the serpentine icon associated with this, likely otherwise fine, package embodies an odd little annoyance to all us structural biochemists: It depicts the DNA helix as left-handed. This is a rare form of DNA at best, most likely an unlucky graphical choice, and causes many nerdy folk to suspect that you don't know what you're doing. If you think i'm nuts (and hey maybe...) there are entire websites devoted to this error, because for some reason it's a common error and makes our eyes bleed [wink]: http://users.fred.net/tds/leftdna/
Other nerdy folks will be happy to grant that an icon is merely that and not intended to be a perfect embodiment of a molecule.
Those folks lack expertise in the domain. Sequences are simply abstract representations of real molecules, and knowledge of sequence means very little without exercising effort and rigor to understand structure and function.
As far as I can tell, this is just a python wrapper for common bioinformatics tools?

I feel like this might not be sophisticated enough for bioinformaticians, but too complex for the casual user or clinician. Unfortunately, proper bioinformatics requires a heafty dose of background knowledge. If you don't understand what you are aligning and filtering, and why, then the results will always just be a shot in the dark.

Actually it's not. It has been written from scratch including the ORM that runs in the background (https://github.com/tariqdaouda/rabaDB). The goal was to have a powerful optimized tool with 0 dependencies that can be easily deployed on any platform. It was designed to be flexible and powerful enough to be appealing to both bioinformaticians and casual users, and it used daily here at the Institute for Research in Immunology and Cancer (www.iric.ca) by professional bioinformaticians, as well as biologists who have learned to program using it.

PyGeno was already used for two peer reviewed articles:

-Impact of genomic polymorphisms on the repertoire of human MHC class I-associated peptides. Granados, Sriranganadane, Daouda et al. 2014, Nat. Comm

-MHC I-associated peptides preferentially derive from transcripts bearing miRNA response elements. Granados et al. 2012, Blood

And four others are on the way.