/// <summary>
/// Finds matching sequences per the weight matrix model.
/// </summary>
public WmmSequenceResult FindScoringSequences()
{
var returnResult = new WmmSequenceResult()
{
ParametersUsed = this.parameters.Clone()
};
// Scan through sliding window of scan length and calculate the Wmm based score for each instance.
for (int i = 0; i < sequence.Length - scanLength + 1; i++)
{
double score = 0;
for (int j = 0; j < scanLength; j++)
{
score = score + this.parameters.GetWmmScore(sequence[i + j], j);
}
var resultToAdd = new WmmSequenceResultItem
{
DistanceFromCleavageSite = sequence.Length - i,
LogLikelihoodScore = score,
Sequence = sequence.Substring(i, scanLength),
};
returnResult.FoundSequences.Add(resultToAdd);
}
return(returnResult);
}
public Dictionary <int, WmmSequenceResult> FindScoringSequences(int iterationCount)
{
for (int iteration = 1; iteration <= iterationCount; iteration++)
{
// Find all possible Motif instances and their log probability scores.
for (int i = 0; i < sequences.Length; i++)
{
var wmmImpl = new WmmSequenceScanImpl(
parameters,
sequence: sequences[i],
scanLength: this.scanLength);
WmmSequenceResult result = wmmImpl.FindScoringSequences();
resultCollection.Add(i, result);
}
// Calculate hidden variable a.k.a Yij Hat.
foreach (WmmSequenceResult result in resultCollection.Values)
{
double sumOfProbabilities = result.FoundSequences.Sum(s => s.LikelihoodScore);
foreach (WmmSequenceResultItem foundSequence in result.FoundSequences)
{
foundSequence.LatentVariable = foundSequence.LikelihoodScore / sumOfProbabilities;
}
}
}
this.parameters.UpateParameters(resultCollection);
// Execute last iteration with new parameters.
resultCollection.Clear();
for (int i = 0; i < sequences.Length; i++)
{
var wmmImpl = new WmmSequenceScanImpl(
parameters,
sequence: sequences[i],
scanLength: this.scanLength);
WmmSequenceResult result = wmmImpl.FindScoringSequences();
resultCollection.Add(i, result);
}
return(resultCollection);
}
