public void TestMsaBenchMarkOnBralibase()
{
List <float> allQ = new List <float>();
List <float> allTC = new List <float>();
string fileDirectory = @"testData\FASTA\RNA\k10";
DirectoryInfo iD = new DirectoryInfo(fileDirectory);
PAMSAMMultipleSequenceAligner.FasterVersion = false;
PAMSAMMultipleSequenceAligner.UseWeights = false;
PAMSAMMultipleSequenceAligner.UseStageB = false;
PAMSAMMultipleSequenceAligner.NumberOfCores = 2;
MoleculeType mt = MoleculeType.RNA;
SimilarityMatrix similarityMatrix;
int gapOpenPenalty = -20;
int gapExtendPenalty = -5;
int kmerLength = 4;
int numberOfDegrees = 2; //Environment.ProcessorCount;
int numberOfPartitions = 16; // Environment.ProcessorCount * 2;
DistanceFunctionTypes distanceFunctionName = DistanceFunctionTypes.EuclideanDistance;
UpdateDistanceMethodsTypes hierarchicalClusteringMethodName = UpdateDistanceMethodsTypes.Average;
ProfileAlignerNames profileAlignerName = ProfileAlignerNames.NeedlemanWunschProfileAligner;
ProfileScoreFunctionNames profileProfileFunctionName = ProfileScoreFunctionNames.WeightedInnerProductCached;
switch (mt)
{
case (MoleculeType.DNA):
similarityMatrix = new SimilarityMatrix(SimilarityMatrix.StandardSimilarityMatrix.AmbiguousDna);
break;
case (MoleculeType.RNA):
similarityMatrix = new SimilarityMatrix(SimilarityMatrix.StandardSimilarityMatrix.AmbiguousRna);
break;
case (MoleculeType.Protein):
similarityMatrix = new SimilarityMatrix(SimilarityMatrix.StandardSimilarityMatrix.Blosum62);
break;
default:
throw new Exception("Invalid molecular type");
}
foreach (DirectoryInfo fi in iD.GetDirectories())
{
foreach (FileInfo fiii in fi.GetFiles())
{
String filePath = fiii.FullName;
Console.WriteLine(filePath);
ISequenceParser parser = new FastaParser();
IList <ISequence> orgSequences = parser.Parse(filePath);
List <ISequence> sequences = MsaUtils.UnAlign(orgSequences);
int numberOfSequences = orgSequences.Count;
Console.WriteLine("The number of sequences is: {0}", numberOfSequences);
Console.WriteLine("Original unaligned sequences are:");
PAMSAMMultipleSequenceAligner msa = new PAMSAMMultipleSequenceAligner
(sequences, mt, kmerLength, distanceFunctionName, hierarchicalClusteringMethodName,
profileAlignerName, profileProfileFunctionName, similarityMatrix, gapOpenPenalty, gapExtendPenalty,
numberOfPartitions, numberOfDegrees);
Console.WriteLine("Aligned sequences final: {0}", msa.AlignmentScore);
for (int i = 0; i < msa.AlignedSequences.Count; ++i)
{
//Console.WriteLine(msa.AlignedSequences[i].ToString());
}
float scoreQ = MsaUtils.CalculateAlignmentScoreQ(msa.AlignedSequences, orgSequences);
float scoreTC = MsaUtils.CalculateAlignmentScoreTC(msa.AlignedSequences, orgSequences);
allQ.Add(scoreQ);
allTC.Add(scoreTC);
Console.WriteLine("Alignment score Q is: {0}", scoreQ);
Console.WriteLine("Alignment score TC is: {0}", scoreTC);
if (allQ.Count % 1000 == 0)
{
Console.WriteLine(">>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>");
Console.WriteLine("average Q score is: {0}", MsaUtils.Mean(allQ.ToArray()));
Console.WriteLine("average TC score is: {0}", MsaUtils.Mean(allTC.ToArray()));
}
}
}
Console.WriteLine("number of datasets is: {0}", allQ.Count);
Console.WriteLine("average Q score is: {0}", MsaUtils.Mean(allQ.ToArray()));
Console.WriteLine("average TC score is: {0}", MsaUtils.Mean(allTC.ToArray()));
}
public void TestMsaBenchMarkOnBralibase()
{
var allQ = new List <float>();
var allTC = new List <float>();
string fileDirectory = @"TestUtils\Fasta\RNA\k10".TestDir();
DirectoryInfo iD = new DirectoryInfo(fileDirectory);
PAMSAMMultipleSequenceAligner.FasterVersion = false;
PAMSAMMultipleSequenceAligner.UseWeights = false;
PAMSAMMultipleSequenceAligner.UseStageB = false;
PAMSAMMultipleSequenceAligner.NumberOfCores = 2;
var similarityMatrix = new SimilarityMatrix(SimilarityMatrix.StandardSimilarityMatrix.AmbiguousRna);;
int gapOpenPenalty = -20;
int gapExtendPenalty = -5;
int kmerLength = 4;
int numberOfDegrees = 2;
int numberOfPartitions = 16;
DistanceFunctionTypes distanceFunctionName = DistanceFunctionTypes.EuclideanDistance;
UpdateDistanceMethodsTypes hierarchicalClusteringMethodName = UpdateDistanceMethodsTypes.Average;
ProfileAlignerNames profileAlignerName = ProfileAlignerNames.NeedlemanWunschProfileAligner;
ProfileScoreFunctionNames profileProfileFunctionName = ProfileScoreFunctionNames.WeightedInnerProductCached;
foreach (DirectoryInfo fi in iD.GetDirectories())
{
foreach (FileInfo fiii in fi.GetFiles())
{
String filePath = fiii.FullName;
Console.WriteLine($"Loading: {filePath}");
var orgSequences = new FastAParser()
{
Alphabet = AmbiguousRnaAlphabet.Instance
}.Parse(filePath).ToList();
var sequences = MsaUtils.UnAlign(orgSequences);
int numberOfSequences = orgSequences.Count;
Console.WriteLine("The number of sequences is: {0}", numberOfSequences);
PAMSAMMultipleSequenceAligner msa = new PAMSAMMultipleSequenceAligner
(sequences, kmerLength, distanceFunctionName, hierarchicalClusteringMethodName,
profileAlignerName, profileProfileFunctionName, similarityMatrix, gapOpenPenalty, gapExtendPenalty,
numberOfPartitions, numberOfDegrees);
Console.WriteLine("Aligned sequences final: {0}", msa.AlignmentScore);
float scoreQ = MsaUtils.CalculateAlignmentScoreQ(msa.AlignedSequences, orgSequences);
float scoreTC = MsaUtils.CalculateAlignmentScoreTC(msa.AlignedSequences, orgSequences);
Console.WriteLine("Alignment score Q is: {0}", scoreQ);
Console.WriteLine("Alignment score TC is: {0}", scoreTC);
allQ.Add(scoreQ);
allTC.Add(scoreTC);
if (allQ.Count % 1000 == 0)
{
Console.WriteLine(">>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>");
Console.WriteLine("average Q score is: {0}", MsaUtils.Mean(allQ.ToArray()));
Console.WriteLine("average TC score is: {0}", MsaUtils.Mean(allTC.ToArray()));
}
}
}
Console.WriteLine("number of datasets is: {0}", allQ.Count);
Console.WriteLine("average Q score is: {0}", MsaUtils.Mean(allQ.ToArray()));
Console.WriteLine("average TC score is: {0}", MsaUtils.Mean(allTC.ToArray()));
}
public void TestMsaBenchMark()
{
string fileDirectory = @"TestUtils\FASTA\Protein\Balibase\RV911\";
DirectoryInfo iD = new DirectoryInfo(fileDirectory);
PAMSAMMultipleSequenceAligner.FasterVersion = false;
PAMSAMMultipleSequenceAligner.UseWeights = false;
PAMSAMMultipleSequenceAligner.UseStageB = true;
PAMSAMMultipleSequenceAligner.NumberOfCores = 2;
SimilarityMatrix similarityMatrix;
int gapOpenPenalty = -20;
int gapExtendPenalty = -5;
int kmerLength = 4;
int numberOfDegrees = 2; //Environment.ProcessorCount;
int numberOfPartitions = 16; // Environment.ProcessorCount * 2;
DistanceFunctionTypes distanceFunctionName = DistanceFunctionTypes.EuclideanDistance;
UpdateDistanceMethodsTypes hierarchicalClusteringMethodName = UpdateDistanceMethodsTypes.Average;
ProfileAlignerNames profileAlignerName = ProfileAlignerNames.NeedlemanWunschProfileAligner;
ProfileScoreFunctionNames profileProfileFunctionName = ProfileScoreFunctionNames.WeightedInnerProductCached;
similarityMatrix = new SimilarityMatrix(SimilarityMatrix.StandardSimilarityMatrix.Blosum62);
List <float> allQ = new List <float>();
List <float> allTC = new List <float>();
foreach (FileInfo fi in iD.GetFiles())
{
String filePath = fi.FullName;
Console.WriteLine(filePath);
FastAParser parser = new FastAParser(filePath);
parser.Alphabet = AmbiguousProteinAlphabet.Instance;
IList <ISequence> orgSequences = parser.Parse().ToList();
List <ISequence> sequences = MsaUtils.UnAlign(orgSequences);
int numberOfSequences = orgSequences.Count;
Console.WriteLine("The number of sequences is: {0}", numberOfSequences);
Console.WriteLine("Original unaligned sequences are:");
for (int i = 0; i < numberOfSequences; ++i)
{
//Console.WriteLine(sequences[i].ToString());
}
Console.WriteLine("Original aligned sequences are:");
for (int i = 0; i < numberOfSequences; ++i)
{
//Console.WriteLine(orgSequences[i].ToString());
}
PAMSAMMultipleSequenceAligner msa = new PAMSAMMultipleSequenceAligner
(sequences, kmerLength, distanceFunctionName, hierarchicalClusteringMethodName,
profileAlignerName, profileProfileFunctionName, similarityMatrix, gapOpenPenalty, gapExtendPenalty,
numberOfPartitions, numberOfDegrees);
Console.WriteLine("Aligned sequences in stage 1: {0}", msa.AlignmentScoreA);
for (int i = 0; i < msa.AlignedSequencesA.Count; ++i)
{
//Console.WriteLine(msa.AlignedSequencesA[i].ToString());
}
Console.WriteLine("Aligned sequences in stage 2: {0}", msa.AlignmentScoreB);
for (int i = 0; i < msa.AlignedSequencesB.Count; ++i)
{
//Console.WriteLine(msa.AlignedSequencesB[i].ToString());
}
Console.WriteLine("Aligned sequences in stage 3: {0}", msa.AlignmentScoreC);
for (int i = 0; i < msa.AlignedSequencesC.Count; ++i)
{
//Console.WriteLine(msa.AlignedSequencesC[i].ToString());
}
Console.WriteLine("Aligned sequences final: {0}", msa.AlignmentScore);
for (int i = 0; i < msa.AlignedSequences.Count; ++i)
{
//Console.WriteLine(msa.AlignedSequences[i].ToString());
}
float scoreQ = MsaUtils.CalculateAlignmentScoreQ(msa.AlignedSequences, orgSequences);
float scoreTC = MsaUtils.CalculateAlignmentScoreTC(msa.AlignedSequences, orgSequences);
allQ.Add(scoreQ);
allTC.Add(scoreTC);
Console.WriteLine("Alignment score Q is: {0}", scoreQ);
Console.WriteLine("Alignment score TC is: {0}", scoreTC);
((FastAParser)parser).Dispose();
}
Console.WriteLine("Number of datasets is: {0}", allQ.Count);
Console.WriteLine("average Q score is: {0}", MsaUtils.Mean(allQ.ToArray()));
Console.WriteLine("average TC score is: {0}", MsaUtils.Mean(allTC.ToArray()));
}
public void TestMsaBenchMarkOnSABmark()
{
List <float> allQ = new List <float>();
List <float> allTC = new List <float>();
string fileDirectory = @"TestUtils\Fasta\Protein\SABmark".TestDir();
DirectoryInfo iD = new DirectoryInfo(fileDirectory);
PAMSAMMultipleSequenceAligner.FasterVersion = false;
PAMSAMMultipleSequenceAligner.UseWeights = false;
PAMSAMMultipleSequenceAligner.UseStageB = true;
PAMSAMMultipleSequenceAligner.NumberOfCores = 2;
SimilarityMatrix similarityMatrix;
int gapOpenPenalty = -13;
int gapExtendPenalty = -5;
int kmerLength = 3;
int numberOfDegrees = 2; //Environment.ProcessorCount;
int numberOfPartitions = 16; // Environment.ProcessorCount * 2;
DistanceFunctionTypes distanceFunctionName = DistanceFunctionTypes.EuclideanDistance;
UpdateDistanceMethodsTypes hierarchicalClusteringMethodName = UpdateDistanceMethodsTypes.Average;
ProfileAlignerNames profileAlignerName = ProfileAlignerNames.NeedlemanWunschProfileAligner;
ProfileScoreFunctionNames profileProfileFunctionName = ProfileScoreFunctionNames.WeightedInnerProduct;
similarityMatrix = new SimilarityMatrix(SimilarityMatrix.StandardSimilarityMatrix.Blosum62);
foreach (DirectoryInfo fi in iD.GetDirectories())
{
foreach (DirectoryInfo fii in fi.GetDirectories())
{
foreach (FileInfo fiii in fii.GetFiles())
{
String filePath = fiii.FullName;
Console.WriteLine(filePath);
FastAParser parser = new FastAParser();
IList <ISequence> orgSequences = parser.Parse(filePath).ToList();
List <ISequence> sequences = MsaUtils.UnAlign(orgSequences);
int numberOfSequences = orgSequences.Count;
Console.WriteLine("The number of sequences is: {0}", numberOfSequences);
Console.WriteLine("Original unaligned sequences are:");
PAMSAMMultipleSequenceAligner msa = new PAMSAMMultipleSequenceAligner
(sequences, kmerLength, distanceFunctionName, hierarchicalClusteringMethodName,
profileAlignerName, profileProfileFunctionName, similarityMatrix, gapOpenPenalty, gapExtendPenalty,
numberOfPartitions, numberOfDegrees);
Console.WriteLine("Aligned sequences final: {0}", msa.AlignmentScore);
for (int i = 0; i < msa.AlignedSequences.Count; ++i)
{
//Console.WriteLine(msa.AlignedSequences[i].ToString());
}
float scoreQ = MsaUtils.CalculateAlignmentScoreQ(msa.AlignedSequences, orgSequences);
float scoreTC = MsaUtils.CalculateAlignmentScoreTC(msa.AlignedSequences, orgSequences);
allQ.Add(scoreQ);
allTC.Add(scoreTC);
Console.WriteLine("Alignment score Q is: {0}", scoreQ);
Console.WriteLine("Alignment score TC is: {0}", scoreTC);
if (allQ.Count % 1000 == 0)
{
Console.WriteLine(">>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>");
Console.WriteLine("average Q score is: {0}", MsaUtils.Mean(allQ.ToArray()));
Console.WriteLine("average TC score is: {0}", MsaUtils.Mean(allTC.ToArray()));
}
}
}
}
Console.WriteLine("average Q score is: {0}", MsaUtils.Mean(allQ.ToArray()));
Console.WriteLine("average TC score is: {0}", MsaUtils.Mean(allTC.ToArray()));
}