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| Description |
Quality-aware alignments
Generally, quality data are ignored for alignment/pattern searching
like Smith-Waterman, Needleman-Wunsch, or BLAST(p|n|x). I believe
that accounting for quality will at the very least affect things like
BLAST statistics, and e.g. is crucial for good EST annotation using Blastx.
This module performs sequences alignments, takes quality values into
account.
See also http://bioinformatics.oxfordjournals.org/cgi/content/abstract/btn052v1.
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| Synopsis |
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| local_score :: QualMx t Double -> (Double, Double) -> Sequence t -> Sequence t -> Double | | | local_align :: QualMx t Double -> (Double, Double) -> Sequence t -> Sequence t -> (Double, EditList) | | | global_score :: QualMx t Double -> (Double, Double) -> Sequence t -> Sequence t -> Double | | | global_align :: QualMx t Double -> (Double, Double) -> Sequence t -> Sequence t -> (Double, EditList) | | | overlap_score :: QualMx t Double -> (Double, Double) -> Sequence t -> Sequence t -> Double | | | overlap_align :: QualMx t Double -> (Double, Double) -> Sequence t -> Sequence t -> (Double, EditList) | | | qualMx :: Qual -> Qual -> (Chr, Chr) -> Double | | | test :: IO () |
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| Smith-Waterman
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| Locally optimal alignment with affine gaps, i.e. best infix match.
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| Calculate local edit distance (Smith-Waterman alignment score)
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| Calculate local alignment (Smith-Waterman)
(can we replace uncurry max' with fst - a local alignment must always end on a subst, no?)
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| Needleman-Wunsch
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| Globally optimal alignment with affine gaps, the whole sequences are matched.
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| Calculate global edit distance (Needleman-Wunsch alignment score)
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| Calculate global alignment (Needleman-Wunsch)
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| Overlapping alignment.
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| The suffix of one sequence matches a prefix of another.
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| Calucalte best overlap score, where gaps at the edges are free
The starting point is like for local score (0 cost for initial indels),
the result is the maximum anywhere in the last column or bottom row of the matrix.
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| Calucalte best overlap score, where gaps at the edges are free
The starting point is like for local score (0 cost for initial indels),
the result is the maximum anywhere in the last column or bottom row of the matrix.
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| Matrix construction
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| Interactive testing of alignments
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| Produced by Haddock version 2.6.1 |
