PEP8, refactor IEDB

[iskandr]

• Using single instance of datacache.Cache instead of sprinkling hard-coded subdir arguments around multiple download points
• Split iedb.py into a sub-package called iedb with modules mhc, tcell, alleles.
• Added a memoization to major functions in iedb
• Lots of misc. PEP8 fixes
• Got rid of tcga peptides functions, which used hackish MAF amino acid change parsing (can use Varcode in the future)

[arahuja]

Comments from the review on Reviewable.io

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^{pepdata/common.py, line 38 [r1] (raw file):}
Does it matter here if one of the two is hashable?

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^{pepdata/hiv_frahm.py, line 31 [r1] (raw file):}
Does read_csv work here or should it be read_html?

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^{pepdata/iedb/alleles.py, line 86 [r1] (raw file):}
Is this just debugging?

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^{pepdata/iedb/common.py, line 35 [r1] (raw file):}
Is there a reason to do the aggregation individually and building a new dataframe instead of df.agg({..})?

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^{pepdata/iedb/mhc.py, line 123 [r1] (raw file):}
Can this be configurable?

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^{pepdata/iedb/mhc.py, line 232 [r1] (raw file):}
quotes?

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^{pepdata/iedb/mhc.py, line 235 [r1] (raw file):}
quotes?

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^{pepdata/iedb/tcell.py, line 151 [r1] (raw file):}
Can this just be a map on the series?
mhc.map(lambda allele: 1 if ...)

maybe no reason to change it.

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[iskandr]

Comments from the review on Reviewable.io

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^{pepdata/common.py, line 38 [r1] (raw file):}
I was thinking of trying to handle that, do you think it's worth it?

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^{pepdata/hiv_frahm.py, line 31 [r1] (raw file):}
This is an oddity of how I wrote datacache, it'll pull a table out of an HTML file by default and give you a CSV. I changed the filename to be "frahm.csv" and added an issue to datacache to not perform all that magic under the hood: openvax/datacache#24

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^{pepdata/iedb/alleles.py, line 86 [r1] (raw file):}
Yep, getting rid of it

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^{pepdata/iedb/common.py, line 35 [r1] (raw file):}
I guess the alternative is something like:

agg = groups.agg({'value' : np.mean, 'count' : lambda x: len(x), 'pos' : np.sum})
agg['neg'] = agg['count'] - agg['pos']
if min_count:
    mask = agg['counts'] >= min_count
    agg = agg[mask]
return agg

Would that work and do you think it's clearer?

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^{pepdata/iedb/mhc.py, line 123 [r1] (raw file):}
Added a only_standard_amino_acids option which defaults to True

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^{pepdata/iedb/tcell.py, line 151 [r1] (raw file):}
That logic is a bit too large to fit into a lambda, so I'd have to add an inline function, which I'm not sure makes the code any clearer.

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[arahuja]

Comments from the review on Reviewable.io

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^{pepdata/iedb/common.py, line 35 [r1] (raw file):}
Actually maybe I misunderstood what was going on here - was this getting averages and counts for many columns? If so agg probably won't be clearer

it'd be .agg({'col': [np.mean, np.sum'], 'col2': ..

I guess its not clear what is in peptides so maybe a comment?

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[iskandr]

Comments from the review on Reviewable.io

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^{pepdata/iedb/common.py, line 35 [r1] (raw file):}
Added a docstring to hopefully clear up what this function actually does.

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