Class | Description |
---|---|
CombinedScorer |
Given two Scorers whose results are presumed to be independent and based on log probabilities, returns the probability of seeing both
scores (ie, the intersection of the probabilities.
|
ConservationICScorer |
Measures the conservation of a motif m as the information content of m, as defined by Stormo in all his papers.
|
ConservationRatioScorer |
Measures the conservation of a motif m as the percentage of approximate instances of m that are exact matches to m.
|
CoverageScorer | |
GroupScorer |
Used to calculate sig scores for motifs or motif lists using two motif finders, one to represent the entire relevant biological sequence,
and another to represent the group of subsequences of specific importance.
|
KSGroupScorer |
A scorer based on the probability that a motif (or motif list) is distributed genomically according to some given CDF.
|
KSScorer |
A scorer based on the probability that a motif (or motif list) is distributed genomically according to some given CDF.
|
LogOccurrenceScorer |
An occurrence scorer is a group scorer that scores motifs based on the number of times they occur in the sequence and in the group.
|
MarkovMaxOrderScorer |
A ratio scorer that returns the log_2 ratio of the observed count over the expected count.
|
MaximalMatcher |
This class is designed primarily for phi scoring, but in general it deals with int[]'s and how they overlap each other.
|
MotifFilter |
This is an early rendition of a MotifFilter that will have a bunch of Scorers and will score a motif by all the scorers and come up with
some composite score.
|
OccurrenceKSScorer |
Combines Occurrence and KS
|
OccurrenceScorer |
An occurrence scorer is a group scorer that scores motifs based on the number of times they occur in the sequence and in the group.
|
PhiComparator |
A
SequenceComparator that uses phi scores to determine equivalence. |
RatioScorer |
A ratio scorer that takes two motif finders, and calculates scores as the log_2 ratio of the occurrence of a motif in the "group" motif
finder over the "genomic" motif finder.
|
RelativeEntropyScorer |
Measures the conservation of a motif m as the relative entropy of m around it's neighbors in the test motif finder versus the reference
motif finder.
|
Scorer |
Used to calculate sig score for motifs or motif lists using a given motif finder.
|
ScorerFactory |
Contains static methods to create motif scorers.
|
ZScoreScorer |
This is a wrapper class around Scorer that is itself a Scorer.
|
Scorer
is the parent of all Scorers, and
GroupScorer
is a subclass of
Scorer
and the parent of all Scorers that maintain a notion of group and background.
Scorer
contains a defined group of core methods:
Scorer.computePrior(Motif)
: Computes the prior (aka Bonferonni) of a Motif.
also exists for MotifLists.
Scorer.calculateScore(Motif)
: This is abstract and must be defined by all
Scorers. This is after all what makes each scorer unique.
Scorer.setScore(Motif)
: Calls calculateScore()
then sets the
score field of the Motif to the result. This is the most often used method outside the class.
Scorer.setScores(Motif[])
: Calls setScore()
on all Motifs in
the array.
Scorer.computePhi(Motif, Motif)
: Computes the phi score of the two Motifs
using the internal MotifFinder.
calculateScore(Motif)
and
calculateScore(MotifList)
. Of course, some scorers are sufficiently complicated to warrant some extra methods.
Scorers can be created dynamically using reflection by using the ScorerFactory
class. In order for a new scorer to work with this factory, it must implement the constructor:
<ClassName>(MotifFinder, boolean, int)This can usually be done by a simple call to
super(MotifFinder, boolean, int)
.
GroupScorers maintain a notion of group and genome, or background. At the top level, the only difference is in
the constructor, which takes two Motif Finders, one for the group and one for the genome. Several of the utility methods
are overridden by GroupScorer
to use the group-based Motif Finder. For example, the phi score methods use
the group Motif Finder to compute the phi score, and getMotifFinder()
and setMotifFinder()
work with the group Motif Finder. To compensate for this, methods exist to get and set the genomic Motif Finder.
A number of scorers have been written, but the two most commonly used are OccurrenceScorer
, which scores motifs on the likelihood of seeing a given number of
occurrences in the group given the number of occurrences in the genome (the Sig value referred to in the papers),
and OccurrenceKSScorer
, which combies OccurrenceScorer
with KSGroupScorer
to provide a joint probability that a motif will be so over-represented and
positionally restricted. This combination scorer utilizes CombinedScorer
, which
provides a general framework for linearly combining scorers. Other combined scorers exist, and more can be easily
created using CombinedScorer
. Use OccurrenceKSScorer
as a reference when writing new combined
scorers.
Finally, MaximalMatcher
provides Phi scoring functionality. This is a rather
archane class.