Caching of transcript protein links received from the NCBI Entrez
service is a typical use case for Redis. This implements this cache
in Redis and removes all use of our original database table.

An Alembic migration copies all existing links from the database to
Redis. The original `TranscriptProteinLink` database table is not
dropped. This will be done in a future migration to ensure running
processes don't error and to provide a rollback scenario.

We also remove the expiration of links (originally defaulting to 30
days), since we don't expect them to ever change. Negative links
(caching a 'not found' result from Entrez) *are* still expiring,
but with a longer default of 30 days (was 5 days).

The configuration setting for the latter was renamed, yielding the
following changes in the default configuration settings.

Removed default settings:

    # Expiration time for transcript<->protein links from the NCBI (in seconds).
    PROTEIN_LINK_EXPIRATION = 60 * 60 * 24 * 30

    # Expiration time for negative transcript<->protein links from the NCBI (in
    # seconds).
    NEGATIVE_PROTEIN_LINK_EXPIRATION = 60 * 60 * 24 * 5

Added default setting:

    # Cache expiration time for negative transcript<->protein links from the NCBI
    # (in seconds).
    NEGATIVE_LINK_CACHE_EXPIRATION = 60 * 60 * 24 * 30

The alternative variant protein sequence translated from a
non-reference start codon (created by the variant), was not
color-diffed as normal variant protein sequences are.

In the process we also rename the `oldprotein` and `newprotein`
fields in the output object to `oldProtein` and `newProtein` to
be more consistent with other field names.

In the case of an alternative start codon (in the reference CDS),
protein changes were not visualised. This is fixed and a WALTSTART
warning is also issued.

Also, if a new non-reference start codon is created by the variant,
visualise this as such.

In case of an alternative start codon, the variant CDS was not
translated to a protein starting with M. This caused the protein
description machinery to conclude a variant affecting the start
codon, hence reporting `p.?`.

We fix this by always translating the start codon to M (except
when the variant actually affects it).

Example: `NM_024426.4:c.1107A>G` (a synomymous mutation) should
yield `NM_024426.4(WT1_i001):p.(=)`, not `p.?`. The start codon
for that protein is `CTG`.

When a variant results in a frame shift or extension and we don't
see a new stop codon in the RNA, the protein description should use
the notation for an uncertain stop codon, e.g., `p.(Gln730Profs*?)`
instead of `p.(Gln730Profs*96)` where 96 is just the last codon in
our transcript [1].

To detect this, we now use `to_stop=False` in our `.translate()`
calls, since that will explicitely return `*` characters for stop
codons.

We also slightly fix the coloring of changes in the protein sequence
where previously changed stop codon characters where not included.

[1] http://www.hgvs.org/mutnomen/FAQ.html#nostop

Issue #50 showed a problem in our file encoding detection, caused
by our cut-off for the confidence as reported by the cchardet [1]
library:

    >>> import cchardet
    >>> s = u'NM_000052.4:c.2407\u20132A>G'
    >>> b = s.encode('WINDOWS-1252')
    >>> cchardet.detect(b)
    {'confidence': 0.5, 'encoding': u'WINDOWS-1252'}

We require a confidence stictly greater than 0.5 and default to
UTF8 otherwise.

If, however, we try the same thing using the chardet [2] library,
we get a higher confidence for the same string:

    >>> import chardet
    >>> chardet.detect(b)
    {'confidence': 0.73, 'encoding': 'windows-1252'}

So the two obvious ways to solve this are:

1. Lower the confidence threshold.
2. Use chardet instead of cchardet.

We implement the second solution here, since it also removes a C
library dependency and we are not worried by performance.

Of course the detected encoding remains a guess which can still
be wrong!

[1] https://github.com/PyYoshi/cChardet
[2] https://github.com/chardet/chardet

Fixes #50

Adds a `EXTRACTOR_MAX_INPUT_LENGTH` configuration setting, defaulting
to 50 Kbp.

Jeroen F.J. Laros authored 9 years ago and Vermaat committed 9 years ago

We can now compare two sequences by supplying their sequence strings,
accession numbers, or uploaded file.

This is a work in progress as there still seem to be some bugs. For example,
some unit tests fail due to incorrect descriptions generated and others fail
due to a crash.

Many genbank reference files contain more than one gene, especially
slices from an assembly. Some of these genes may be incomplete in
the reference file (i.e., either start or end exceeds the outer
coordinates). We cannot really do anything with these genes, so we
discard them during parsing.

Given a gene symbol and optional genome build, this returns the location
of the gene.

Primary motivation for this is LOVD, where it will be used in combination
with sliceChromsome as an alternative for sliceChromosomeByGene which only
works on the fixed Ensembl genome build.