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- AlignAce
- MetaAce
class AlignAce |
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################################################################################
# AlignAce #
# Execute, Load, and analyze AlignACE output #
################################################################################
Usage:
theAce = AlignAce.AlignAce('filename.fsa',width=10)
-or-
theAce = AlignAce.AlginAce('filename.ace')
The first form executes AlignACE with the specificied input sequences, and the second
is used to parse alignace output from a previous run.
Typically, the user is only interested in the ".motifs" member variable, which contains
a list of all the discovered Motifs (as Motif objects).
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Methods defined here:
- __init__(self, file='', width=10, args='', seed='')
- __repr__(self)
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class MetaAce |
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Usage: theMetaAce = AlignAce.MetaAce(fastafile, width=10, iterations = 5, gcback=0.38)
Class to invoke AlignACE many times and combine the results. A random number
generator is used to ensure that AlignACE is seeded differently each time.
Typically, the user is only interested in the ".results" member variable, which contains
a list of all the discovered Motifs (as Motif objects).
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Methods defined here:
- __init__(self, fastafile='', width=10, iterations=5, gcback=0.38)
- flatten(self, thresh=0.5)
- flatten(thresh=0.5)
This function does some messy reductions in metaACE lists, to cut the number of
identical motifs reported. A better solution is to use one of the clustering
methods elsewhere in the TAMO package.
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