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def | __init__ (s, dver, gc, ref, alt, strand="+", rsID="", normalize=True) |
| Constructor. More...
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def | __str__ (s) |
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def | __eq__ (s, obj) |
| The equality operator. More...
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def | IsChanged (s) |
| Have the input data changed during normalization? More...
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def | GetDBSNPID (s) |
| Get dbSNP ID. More...
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def | Reverse (s) |
| Generate an object for the reverse strand. More...
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def | Original (s) |
| Get an object with the original, unnormalized data. More...
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def | __init__ (s, dver, gc) |
| Constructor. More...
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def | IsValid (s) |
| Is this a valid object? More...
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def | GetChrom (s) |
| Get the chromosome name. More...
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def | GetStart (s) |
| Get the start coordinate of the variant. More...
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def | GetEnd (s) |
| Get the end coordinate of the variant. More...
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def | GetBuild (s) |
| Get the build version. More...
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def | GetCoordString (s) |
| Get the coordinate string of the variant. More...
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Minimalistic form of a variant.
This class attempts to represent variants in a minimalistic, normalized
form. Given the many possibilities to represent a single variant, it is
clear that there is no unique way to accomplish this. The class has been
designed to accept input from VCF-derived variants (eg. ClinVar), Ensembl,
and HGMD, which returns the mutation on the reading strand compared to
dbSNP, which almost always refers to the forward strand. Instances of this
class can be compared with the @c == operator, which is one of the main
goals of its implementation.
Comparison depends on the objects to be compared. If the objects belong to
the same class, the __eq__ method is called for this class. However, if
object @c a and @c c are instances of CAlleleVariant and
CCoordinateVariant, respectively, the comparison operator of the less
specialized class will be used (that is CCoordinateVariant in our case).
Given a variant, we remove redundancy by chopping basepairs from the 5'
and the 3' termini. One should especially be aware that using this class
for an insertion with a reference string (especially useful if it
indicates the reverse strand), there will be information loss due to
normalization.