public void TestMuscleMultipleSequenceAlignmentRunningTime() { string filepath = @"TestUtils\FASTA\RunningTime\BOX246.xml.afa"; // Test on DNA benchmark dataset FastAParser parser = new FastAParser(filepath); IList <ISequence> orgSequences = parser.Parse().ToList(); List <ISequence> sequences = MsaUtils.UnAlign(orgSequences); //filepath = @"TestUtils\FASTA\RunningTime\12_raw.afa"; //List<ISequence> sequences = parser.Parse(filepath); int numberOfSequences = orgSequences.Count; Console.WriteLine("Original sequences are:"); for (int i = 0; i < numberOfSequences; ++i) { Console.WriteLine(new string(sequences[i].Select(a => (char)a).ToArray())); } Console.WriteLine("Benchmark sequences are:"); for (int i = 0; i < numberOfSequences; ++i) { Console.WriteLine(new string(orgSequences[i].Select(a => (char)a).ToArray())); } PAMSAMMultipleSequenceAligner.FasterVersion = true; PAMSAMMultipleSequenceAligner.UseWeights = false; PAMSAMMultipleSequenceAligner.UseStageB = false; PAMSAMMultipleSequenceAligner.NumberOfCores = 2; int gapOpenPenalty = -13; int gapExtendPenalty = -5; int kmerLength = 2; 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.InnerProductFast; SimilarityMatrix similarityMatrix = new SimilarityMatrix(SimilarityMatrix.StandardSimilarityMatrix.Blosum62); PAMSAMMultipleSequenceAligner msa = new PAMSAMMultipleSequenceAligner (sequences, kmerLength, distanceFunctionName, hierarchicalClusteringMethodName, profileAlignerName, profileProfileFunctionName, similarityMatrix, gapOpenPenalty, gapExtendPenalty, numberOfPartitions, numberOfDegrees); Console.WriteLine("The number of partitions is: {0}", numberOfPartitions); Console.WriteLine("The number of degrees is: {0}", numberOfDegrees); Console.WriteLine("Alignment score Q is: {0}", MsaUtils.CalculateAlignmentScoreQ(msa.AlignedSequences, orgSequences)); Console.WriteLine("Alignment score TC is: {0}", MsaUtils.CalculateAlignmentScoreTC(msa.AlignedSequences, orgSequences)); Console.WriteLine("Benchmark SPS score is: {0}", MsaUtils.MultipleAlignmentScoreFunction(orgSequences, similarityMatrix, gapOpenPenalty, gapExtendPenalty)); Console.WriteLine("Aligned sequences in stage 1: {0}", msa.AlignmentScoreA); for (int i = 0; i < msa.AlignedSequencesA.Count; ++i) { Console.WriteLine(new string(msa.AlignedSequencesA[i].Select(a => (char)a).ToArray())); } Console.WriteLine("Alignment score Q is: {0}", MsaUtils.CalculateAlignmentScoreQ(msa.AlignedSequencesA, orgSequences)); Console.WriteLine("Alignment score TC is: {0}", MsaUtils.CalculateAlignmentScoreTC(msa.AlignedSequencesA, orgSequences)); Console.WriteLine("Aligned sequences in stage 2: {0}", msa.AlignmentScoreB); for (int i = 0; i < msa.AlignedSequencesB.Count; ++i) { Console.WriteLine(new string(msa.AlignedSequencesB[i].Select(a => (char)a).ToArray())); } Console.WriteLine("Alignment score Q is: {0}", MsaUtils.CalculateAlignmentScoreQ(msa.AlignedSequencesB, orgSequences)); Console.WriteLine("Alignment score TC is: {0}", MsaUtils.CalculateAlignmentScoreTC(msa.AlignedSequencesB, orgSequences)); Console.WriteLine("Aligned sequences in stage 3: {0}", msa.AlignmentScoreC); for (int i = 0; i < msa.AlignedSequencesC.Count; ++i) { Console.WriteLine(new string(msa.AlignedSequencesC[i].Select(a => (char)a).ToArray())); } Console.WriteLine("Alignment score Q is: {0}", MsaUtils.CalculateAlignmentScoreQ(msa.AlignedSequencesC, orgSequences)); Console.WriteLine("Alignment score TC is: {0}", MsaUtils.CalculateAlignmentScoreTC(msa.AlignedSequencesC, orgSequences)); Console.WriteLine("Aligned sequences final: {0}", msa.AlignmentScore); for (int i = 0; i < msa.AlignedSequences.Count; ++i) { Console.WriteLine(new string(msa.AlignedSequences[i].Select(a => (char)a).ToArray())); } Console.WriteLine("Alignment score Q is: {0}", MsaUtils.CalculateAlignmentScoreQ(msa.AlignedSequences, orgSequences)); Console.WriteLine("Alignment score TC is: {0}", MsaUtils.CalculateAlignmentScoreTC(msa.AlignedSequences, orgSequences)); ((FastAParser)parser).Dispose(); }
public void TestMsaBenchMarkLargeDataset() { // Test on DNA benchmark dataset ISequenceParser parser = new FastaParser(); string filepath = @"testdata\FASTA\Protein\Balibase\RV913\BOX032.xml.afa"; IList <ISequence> orgSequences = parser.Parse(filepath); IList <ISequence> sequences = MsaUtils.UnAlign(orgSequences); int numberOfSequences = orgSequences.Count; String outputFilePath = @"tempBOX032.xml.afa"; StreamWriter writer = new StreamWriter(outputFilePath, true); foreach (ISequence sequence in sequences) { writer.WriteLine(">" + sequence.ID); // write sequence BasicDerivedSequence derivedSeq = new BasicDerivedSequence(sequence, false, false, 0, 0); for (int lineStart = 0; lineStart < sequence.Count; lineStart += 60) { derivedSeq.RangeStart = lineStart; derivedSeq.RangeLength = Math.Min(60, sequence.Count - lineStart); writer.WriteLine(derivedSeq.ToString()); } writer.Flush(); } writer.Close(); sequences.Clear(); sequences = parser.Parse(outputFilePath); Console.WriteLine("Original sequences are:"); for (int i = 0; i < numberOfSequences; ++i) { Console.WriteLine(sequences[i].ToString()); } Console.WriteLine("Benchmark sequences are:"); for (int i = 0; i < numberOfSequences; ++i) { Console.WriteLine(orgSequences[i].ToString()); } PAMSAMMultipleSequenceAligner.FasterVersion = false; PAMSAMMultipleSequenceAligner.UseWeights = false; PAMSAMMultipleSequenceAligner.UseStageB = true; PAMSAMMultipleSequenceAligner.NumberOfCores = 2; int gapOpenPenalty = -13; int gapExtendPenalty = -5; int kmerLength = 3; int numberOfDegrees = 2; //Environment.ProcessorCount; int numberOfPartitions = 16; // Environment.ProcessorCount * 2; SimilarityMatrix similarityMatrix = new SimilarityMatrix(SimilarityMatrix.StandardSimilarityMatrix.Blosum62); DistanceFunctionTypes distanceFunctionName = DistanceFunctionTypes.EuclideanDistance; UpdateDistanceMethodsTypes hierarchicalClusteringMethodName = UpdateDistanceMethodsTypes.Average; ProfileAlignerNames profileAlignerName = ProfileAlignerNames.NeedlemanWunschProfileAligner; ProfileScoreFunctionNames profileProfileFunctionName = ProfileScoreFunctionNames.WeightedInnerProduct; PAMSAMMultipleSequenceAligner msa = new PAMSAMMultipleSequenceAligner (sequences, MoleculeType.Protein, kmerLength, distanceFunctionName, hierarchicalClusteringMethodName, profileAlignerName, profileProfileFunctionName, similarityMatrix, gapOpenPenalty, gapExtendPenalty, numberOfPartitions, numberOfDegrees); Console.WriteLine("Benchmark SPS score is: {0}", MsaUtils.MultipleAlignmentScoreFunction(orgSequences, similarityMatrix, gapOpenPenalty, gapExtendPenalty)); 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("Alignment score Q is: {0}", MsaUtils.CalculateAlignmentScoreQ(msa.AlignedSequencesA, orgSequences)); Console.WriteLine("Alignment score TC is: {0}", MsaUtils.CalculateAlignmentScoreTC(msa.AlignedSequencesA, orgSequences)); 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("Alignment score Q is: {0}", MsaUtils.CalculateAlignmentScoreQ(msa.AlignedSequencesB, orgSequences)); Console.WriteLine("Alignment score TC is: {0}", MsaUtils.CalculateAlignmentScoreTC(msa.AlignedSequencesB, orgSequences)); 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("Alignment score Q is: {0}", MsaUtils.CalculateAlignmentScoreQ(msa.AlignedSequencesC, orgSequences)); Console.WriteLine("Alignment score TC is: {0}", MsaUtils.CalculateAlignmentScoreTC(msa.AlignedSequencesC, orgSequences)); Console.WriteLine("Aligned sequences final: {0}", msa.AlignmentScore); for (int i = 0; i < msa.AlignedSequences.Count; ++i) { Console.WriteLine(msa.AlignedSequences[i].ToString()); } Console.WriteLine("Alignment score Q is: {0}", MsaUtils.CalculateAlignmentScoreQ(msa.AlignedSequences, orgSequences)); Console.WriteLine("Alignment score TC is: {0}", MsaUtils.CalculateAlignmentScoreTC(msa.AlignedSequences, orgSequences)); if (File.Exists(outputFilePath)) { File.Delete(outputFilePath); } }
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 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 TestAlignmentScore() { ISequence templateSequence = new Sequence(Alphabets.DNA, "ATGCSWRYKMBVHDN-"); Dictionary <ISequenceItem, int> itemSet = new Dictionary <ISequenceItem, int>(); for (int i = 0; i < templateSequence.Count; ++i) { itemSet.Add(templateSequence[i], i); } Profiles.ItemSet = itemSet; SimilarityMatrix similarityMatrix = new SimilarityMatrix(SimilarityMatrix.StandardSimilarityMatrix.AmbiguousDna); int gapOpenPenalty = -8; int gapExtendPenalty = -1; // Test PairWiseScoreFunction ISequence seqA = new Sequence(Alphabets.DNA, "ACG"); ISequence seqB = new Sequence(Alphabets.DNA, "ACG"); float score = MsaUtils.PairWiseScoreFunction(seqA, seqB, similarityMatrix, gapOpenPenalty, gapExtendPenalty); //Assert.AreEqual(15, score); seqA = new Sequence(Alphabets.DNA, "ACG"); seqB = new Sequence(Alphabets.DNA, "ACC"); score = MsaUtils.PairWiseScoreFunction(seqA, seqB, similarityMatrix, gapOpenPenalty, gapExtendPenalty); //Assert.AreEqual(6, score); seqA = new Sequence(Alphabets.DNA, "AC-"); seqB = new Sequence(Alphabets.DNA, "ACC"); score = MsaUtils.PairWiseScoreFunction(seqA, seqB, similarityMatrix, gapOpenPenalty, gapExtendPenalty); //Assert.AreEqual(2, score); seqA = new Sequence(Alphabets.DNA, "AC--"); seqB = new Sequence(Alphabets.DNA, "ACCG"); score = MsaUtils.PairWiseScoreFunction(seqA, seqB, similarityMatrix, gapOpenPenalty, gapExtendPenalty); //Assert.AreEqual(1, score); seqA = new Sequence(Alphabets.DNA, "A---"); seqB = new Sequence(Alphabets.DNA, "A--C"); score = MsaUtils.PairWiseScoreFunction(seqA, seqB, similarityMatrix, gapOpenPenalty, gapExtendPenalty); //Assert.AreEqual(-3, score); seqA = new Sequence(Alphabets.DNA, "GGGA---AAAATCAGATT"); seqB = new Sequence(Alphabets.DNA, "GGGA--CAAAATCAG---"); score = MsaUtils.PairWiseScoreFunction(seqA, seqB, similarityMatrix, gapOpenPenalty, gapExtendPenalty); //Assert.AreEqual(42, score); seqA = new Sequence(Alphabets.DNA, "GGG---AAAAATCAGATT"); seqB = new Sequence(Alphabets.DNA, "GGGA--CAAAATCAG---"); score = MsaUtils.PairWiseScoreFunction(seqA, seqB, similarityMatrix, gapOpenPenalty, gapExtendPenalty); //Assert.AreEqual(33, score); seqA = new Sequence(Alphabets.DNA, "GGGA---AAAATCAGATT"); seqB = new Sequence(Alphabets.DNA, "GGGAATCAAAATCAG---"); score = MsaUtils.PairWiseScoreFunction(seqA, seqB, similarityMatrix, gapOpenPenalty, gapExtendPenalty); //Assert.AreEqual(40, score); seqA = new Sequence(Alphabets.DNA, "GGGA--CAAAATCAG---"); seqB = new Sequence(Alphabets.DNA, "GGGAATCAAAATCAG---"); score = MsaUtils.PairWiseScoreFunction(seqA, seqB, similarityMatrix, gapOpenPenalty, gapExtendPenalty); //Assert.AreEqual(56, score); // Test MultipleAlignmentScoreFunction List <ISequence> sequences = new List <ISequence>(); seqA = new Sequence(Alphabets.DNA, "GGGA---AAAATCAGATT"); seqB = new Sequence(Alphabets.DNA, "GGGA--CAAAATCAG---"); sequences.Add(seqA); sequences.Add(seqB); score = MsaUtils.MultipleAlignmentScoreFunction(sequences, similarityMatrix, gapOpenPenalty, gapExtendPenalty); Console.WriteLine("alignment score is: {0}", score); for (int i = 0; i < sequences.Count; ++i) { Console.WriteLine(sequences[i].ToString()); } //Assert.AreEqual(42, score); sequences.Add(new Sequence(Alphabets.DNA, "GGGAATCAAAATCAG---")); score = MsaUtils.MultipleAlignmentScoreFunction(sequences, similarityMatrix, gapOpenPenalty, gapExtendPenalty); Console.WriteLine("alignment score is: {0}", score); for (int i = 0; i < sequences.Count; ++i) { Console.WriteLine(sequences[i].ToString()); } //Assert.AreEqual(46, score); sequences[0] = new Sequence(Alphabets.DNA, "GGG---AAAAATCAGATT"); score = MsaUtils.MultipleAlignmentScoreFunction(sequences, similarityMatrix, gapOpenPenalty, gapExtendPenalty); for (int i = 0; i < sequences.Count; ++i) { Console.WriteLine(sequences[i].ToString()); } Console.WriteLine("alignment score is: {0}", score); for (int i = 0; i < sequences.Count; ++i) { Console.WriteLine(sequences[i].ToString()); } //Assert.AreEqual(40, score); // Test CalculateOffset seqA = new Sequence(Alphabets.DNA, "ABCD"); seqB = new Sequence(Alphabets.DNA, "ABCD"); List <int> offset = MsaUtils.CalculateOffset(seqA, seqB); Console.WriteLine("offsets are:"); for (int i = 0; i < offset.Count; ++i) { Console.Write("{0}\t", offset[i]); } seqA = new Sequence(Alphabets.DNA, "A-BCD"); seqB = new Sequence(Alphabets.DNA, "AB-CD"); offset = MsaUtils.CalculateOffset(seqA, seqB); Console.WriteLine("\noffsets are:"); for (int i = 0; i < offset.Count; ++i) { Console.Write("{0}\t", offset[i]); } seqA = new Sequence(Alphabets.DNA, "A-BCD"); seqB = new Sequence(Alphabets.DNA, "----AB-CD"); offset = MsaUtils.CalculateOffset(seqA, seqB); Console.WriteLine("\noffsets are:"); for (int i = 0; i < offset.Count; ++i) { Console.Write("{0}\t", offset[i]); } sequences.Clear(); sequences.Add(seqA); sequences.Add(new Sequence(Alphabets.DNA, "ABBCG")); List <ISequence> sequencesRef = new List <ISequence>(); sequencesRef.Add(seqA); sequencesRef.Add(new Sequence(Alphabets.DNA, "ABBCG")); for (int i = 0; i < sequences.Count; ++i) { offset = MsaUtils.CalculateOffset(sequences[i], sequencesRef[i]); Console.WriteLine("\noffsets are:"); for (int j = 0; j < offset.Count; ++j) { Console.Write("{0}\t", offset[j]); } } Console.WriteLine("Q score is: {0}", MsaUtils.CalculateAlignmentScoreQ(sequences, sequencesRef)); Console.WriteLine("TC score is: {0}", MsaUtils.CalculateAlignmentScoreTC(sequences, sequencesRef)); // Test on one example sequences.Clear(); sequences.Add(new Sequence(Alphabets.DNA, "GGGA---A-AAATCAGATT")); sequences.Add(new Sequence(Alphabets.DNA, "GGGAATCA-AAATCAG---")); sequences.Add(new Sequence(Alphabets.DNA, "GGGAATCA-AAATCAG---")); sequences.Add(new Sequence(Alphabets.DNA, "GGGA---A-A--TC-G---")); sequences.Add(new Sequence(Alphabets.DNA, "GGGAATCA-A--TCAG---")); sequences.Add(new Sequence(Alphabets.DNA, "GGGAATCTTA--TCAG---")); sequences.Add(new Sequence(Alphabets.DNA, "GGGA--CA-AAATCAG---")); sequences.Add(new Sequence(Alphabets.DNA, "GGGA---A-AAATCAGATT")); sequences.Add(new Sequence(Alphabets.DNA, "GGGAATCA-AAATCAG---")); sequences.Add(new Sequence(Alphabets.DNA, "GGGA--CA-AAATCAG---")); gapOpenPenalty = -4; gapExtendPenalty = -1; Console.WriteLine("score is: {0}", MsaUtils.MultipleAlignmentScoreFunction(sequences, similarityMatrix, gapOpenPenalty, gapExtendPenalty)); sequences.Clear(); sequences.Add(new Sequence(Alphabets.DNA, "GGGA---AAAATCAGATT")); sequences.Add(new Sequence(Alphabets.DNA, "GGGAATCAAAATCAG---")); sequences.Add(new Sequence(Alphabets.DNA, "GGGAATCAAAATCAG---")); sequences.Add(new Sequence(Alphabets.DNA, "GGGA-----AATC-G---")); sequences.Add(new Sequence(Alphabets.DNA, "GGGAATC--AATCAG---")); sequences.Add(new Sequence(Alphabets.DNA, "GGGAATCTTA-TCAG---")); sequences.Add(new Sequence(Alphabets.DNA, "GGGA--CAAAATCAG---")); sequences.Add(new Sequence(Alphabets.DNA, "GGGA---AAAATCAGATT")); sequences.Add(new Sequence(Alphabets.DNA, "GGGAATCAAAATCAG---")); sequences.Add(new Sequence(Alphabets.DNA, "GGGA--CAAAATCAG---")); Console.WriteLine("score is: {0}", MsaUtils.MultipleAlignmentScoreFunction(sequences, similarityMatrix, gapOpenPenalty, gapExtendPenalty)); // Test Quick Sort float[] a = new float[5] { 0, 2, 1, 5, 4 }; int[] aIndex = new int[5] { 0, 1, 2, 3, 4 }; MsaUtils.QuickSort(a, aIndex, 0, a.Length - 1); Console.WriteLine("quicksort"); for (int i = 0; i < a.Length; ++i) { Console.WriteLine(a[i]); } for (int i = 0; i < a.Length; ++i) { Console.WriteLine(aIndex[i]); } Console.WriteLine("quicksortM"); a = new float[5] { 0, 2, 1, 5, 4 }; int[] aIndexB = null; MsaUtils.QuickSortM(a, out aIndexB, 0, 4); for (int i = 0; i < a.Length; ++i) { Console.WriteLine(a[i]); } for (int i = 0; i < a.Length; ++i) { Console.WriteLine(aIndexB[i]); } Console.WriteLine("quicksort"); a = new float[5] { 0, 2, 1, 5, 4 }; int[] aIndexC = MsaUtils.CreateIndexArray(a.Length); MsaUtils.QuickSort(a, aIndexC, 0, a.Length - 1); for (int i = 0; i < a.Length; ++i) { Console.WriteLine(aIndexC[i]); } a = new float[5] { 1, 0, 0, 0, 0 }; aIndex = new int[5] { 0, 1, 2, 3, 4 }; MsaUtils.QuickSort(a, aIndex, 0, a.Length - 1); for (int i = 0; i < a.Length; ++i) { Console.WriteLine(a[i]); } for (int i = 0; i < a.Length; ++i) { Console.WriteLine(aIndex[i]); } }
public void TestMsaBenchMarkLargeDataset() { string filepath = @"\TestUtils\BOX032Small.xml.afa"; string filePathObj = Directory.GetCurrentDirectory() + filepath; // Test on DNA benchmark dataset FastAParser parser = new FastAParser(filePathObj); IList <ISequence> orgSequences = parser.Parse().ToList(); IList <ISequence> sequences = MsaUtils.UnAlign(orgSequences); int numberOfSequences = orgSequences.Count; String outputFilePath = @"tempBOX032.xml.afa"; using (StreamWriter writer = new StreamWriter(outputFilePath, true)) { foreach (ISequence sequence in sequences) { writer.WriteLine(">" + sequence.ID); // write sequence for (int lineStart = 0; lineStart < sequence.Count; lineStart += 60) { writer.WriteLine(new String(sequence.Skip(lineStart).Take((int)Math.Min(60, sequence.Count - lineStart)).Select(a => (char)a).ToArray())); } writer.Flush(); } } sequences.Clear(); parser = new FastAParser(outputFilePath); sequences = parser.Parse().ToList(); Console.WriteLine("Original sequences are:"); for (int i = 0; i < numberOfSequences; ++i) { Console.WriteLine(new string(sequences[i].Select(a => (char)a).ToArray())); } Console.WriteLine("Benchmark sequences are:"); for (int i = 0; i < numberOfSequences; ++i) { Console.WriteLine(new string(orgSequences[i].Select(a => (char)a).ToArray())); } PAMSAMMultipleSequenceAligner.FasterVersion = false; PAMSAMMultipleSequenceAligner.UseWeights = false; PAMSAMMultipleSequenceAligner.UseStageB = true; PAMSAMMultipleSequenceAligner.NumberOfCores = 2; int gapOpenPenalty = -13; int gapExtendPenalty = -5; int kmerLength = 3; int numberOfDegrees = 2; //Environment.ProcessorCount; int numberOfPartitions = 16; // Environment.ProcessorCount * 2; SimilarityMatrix similarityMatrix = new SimilarityMatrix(SimilarityMatrix.StandardSimilarityMatrix.Blosum62); DistanceFunctionTypes distanceFunctionName = DistanceFunctionTypes.EuclideanDistance; UpdateDistanceMethodsTypes hierarchicalClusteringMethodName = UpdateDistanceMethodsTypes.Average; ProfileAlignerNames profileAlignerName = ProfileAlignerNames.NeedlemanWunschProfileAligner; ProfileScoreFunctionNames profileProfileFunctionName = ProfileScoreFunctionNames.WeightedInnerProduct; PAMSAMMultipleSequenceAligner msa = new PAMSAMMultipleSequenceAligner (sequences, kmerLength, distanceFunctionName, hierarchicalClusteringMethodName, profileAlignerName, profileProfileFunctionName, similarityMatrix, gapOpenPenalty, gapExtendPenalty, numberOfPartitions, numberOfDegrees); Console.WriteLine("Benchmark SPS score is: {0}", MsaUtils.MultipleAlignmentScoreFunction(orgSequences, similarityMatrix, gapOpenPenalty, gapExtendPenalty)); Console.WriteLine("Aligned sequences in stage 1: {0}", msa.AlignmentScoreA); for (int i = 0; i < msa.AlignedSequencesA.Count; ++i) { Console.WriteLine(new string(msa.AlignedSequencesA[i].Select(a => (char)a).ToArray())); } Console.WriteLine("Alignment score Q is: {0}", MsaUtils.CalculateAlignmentScoreQ(msa.AlignedSequencesA, orgSequences)); Console.WriteLine("Alignment score TC is: {0}", MsaUtils.CalculateAlignmentScoreTC(msa.AlignedSequencesA, orgSequences)); Console.WriteLine("Aligned sequences in stage 2: {0}", msa.AlignmentScoreB); for (int i = 0; i < msa.AlignedSequencesB.Count; ++i) { Console.WriteLine(new string(msa.AlignedSequencesB[i].Select(a => (char)a).ToArray())); } Console.WriteLine("Alignment score Q is: {0}", MsaUtils.CalculateAlignmentScoreQ(msa.AlignedSequencesB, orgSequences)); Console.WriteLine("Alignment score TC is: {0}", MsaUtils.CalculateAlignmentScoreTC(msa.AlignedSequencesB, orgSequences)); Console.WriteLine("Aligned sequences in stage 3: {0}", msa.AlignmentScoreC); for (int i = 0; i < msa.AlignedSequencesC.Count; ++i) { Console.WriteLine(new string(msa.AlignedSequencesC[i].Select(a => (char)a).ToArray())); } Console.WriteLine("Alignment score Q is: {0}", MsaUtils.CalculateAlignmentScoreQ(msa.AlignedSequencesC, orgSequences)); Console.WriteLine("Alignment score TC is: {0}", MsaUtils.CalculateAlignmentScoreTC(msa.AlignedSequencesC, orgSequences)); Console.WriteLine("Aligned sequences final: {0}", msa.AlignmentScore); for (int i = 0; i < msa.AlignedSequences.Count; ++i) { Console.WriteLine(new string(msa.AlignedSequences[i].Select(a => (char)a).ToArray())); } Console.WriteLine("Alignment score Q is: {0}", MsaUtils.CalculateAlignmentScoreQ(msa.AlignedSequences, orgSequences)); Console.WriteLine("Alignment score TC is: {0}", MsaUtils.CalculateAlignmentScoreTC(msa.AlignedSequences, orgSequences)); ((FastAParser)parser).Dispose(); if (File.Exists(outputFilePath)) { File.Delete(outputFilePath); } }
public void TestMuscleMultipleSequenceAlignmentRunningTime() { // Test on DNA benchmark dataset ISequenceParser parser = new FastaParser(); //string filepath = @"testdata\FASTA\RunningTime\122.afa"; string filepath = @"testdata\FASTA\RunningTime\BOX246.xml.afa"; MoleculeType mt = MoleculeType.Protein; IList <ISequence> orgSequences = parser.Parse(filepath); List <ISequence> sequences = MsaUtils.UnAlign(orgSequences); //filepath = @"testdata\FASTA\RunningTime\12_raw.afa"; //List<ISequence> sequences = parser.Parse(filepath); int numberOfSequences = orgSequences.Count; Console.WriteLine("Original sequences are:"); for (int i = 0; i < numberOfSequences; ++i) { Console.WriteLine(sequences[i].ToString()); } Console.WriteLine("Benchmark sequences are:"); for (int i = 0; i < numberOfSequences; ++i) { Console.WriteLine(orgSequences[i].ToString()); } PAMSAMMultipleSequenceAligner.FasterVersion = true; PAMSAMMultipleSequenceAligner.UseWeights = false; PAMSAMMultipleSequenceAligner.UseStageB = false; PAMSAMMultipleSequenceAligner.NumberOfCores = 2; int gapOpenPenalty = -13; int gapExtendPenalty = -5; int kmerLength = 2; 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.InnerProductFast; SimilarityMatrix similarityMatrix = null; 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"); } PAMSAMMultipleSequenceAligner msa = new PAMSAMMultipleSequenceAligner (sequences, mt, kmerLength, distanceFunctionName, hierarchicalClusteringMethodName, profileAlignerName, profileProfileFunctionName, similarityMatrix, gapOpenPenalty, gapExtendPenalty, numberOfPartitions, numberOfDegrees); Console.WriteLine("The number of partitions is: {0}", numberOfPartitions); Console.WriteLine("The number of degrees is: {0}", numberOfDegrees); Console.WriteLine("Alignment score Q is: {0}", MsaUtils.CalculateAlignmentScoreQ(msa.AlignedSequences, orgSequences)); Console.WriteLine("Alignment score TC is: {0}", MsaUtils.CalculateAlignmentScoreTC(msa.AlignedSequences, orgSequences)); Console.WriteLine("Benchmark SPS score is: {0}", MsaUtils.MultipleAlignmentScoreFunction(orgSequences, similarityMatrix, gapOpenPenalty, gapExtendPenalty)); 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("Alignment score Q is: {0}", MsaUtils.CalculateAlignmentScoreQ(msa.AlignedSequencesA, orgSequences)); Console.WriteLine("Alignment score TC is: {0}", MsaUtils.CalculateAlignmentScoreTC(msa.AlignedSequencesA, orgSequences)); 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("Alignment score Q is: {0}", MsaUtils.CalculateAlignmentScoreQ(msa.AlignedSequencesB, orgSequences)); Console.WriteLine("Alignment score TC is: {0}", MsaUtils.CalculateAlignmentScoreTC(msa.AlignedSequencesB, orgSequences)); 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("Alignment score Q is: {0}", MsaUtils.CalculateAlignmentScoreQ(msa.AlignedSequencesC, orgSequences)); Console.WriteLine("Alignment score TC is: {0}", MsaUtils.CalculateAlignmentScoreTC(msa.AlignedSequencesC, orgSequences)); Console.WriteLine("Aligned sequences final: {0}", msa.AlignmentScore); for (int i = 0; i < msa.AlignedSequences.Count; ++i) { Console.WriteLine(msa.AlignedSequences[i].ToString()); } Console.WriteLine("Alignment score Q is: {0}", MsaUtils.CalculateAlignmentScoreQ(msa.AlignedSequences, orgSequences)); Console.WriteLine("Alignment score TC is: {0}", MsaUtils.CalculateAlignmentScoreTC(msa.AlignedSequences, orgSequences)); }
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 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())); }
public void TestMsaBenchMarkLargeDataset() { // Test on DNA benchmark dataset string filePathObj = @"TestUtils\BOX032Small.xml.afa".TestDir(); var orgSequences = new FastAParser().Parse(filePathObj).ToList(); var sequences = MsaUtils.UnAlign(orgSequences); int numberOfSequences = orgSequences.Count; Assert.AreEqual(numberOfSequences, sequences.Count); string outputFilePath = Path.GetTempFileName(); try { using (StreamWriter writer = new StreamWriter(outputFilePath, true)) { foreach (ISequence sequence in sequences) { // write sequence writer.WriteLine(">" + sequence.ID); for (int lineStart = 0; lineStart < sequence.Count; lineStart += 60) { writer.WriteLine(new String(sequence.Skip(lineStart).Take((int)Math.Min(60, sequence.Count - lineStart)).Select(a => (char)a).ToArray())); } writer.Flush(); } } sequences = new FastAParser().Parse(outputFilePath).ToList(); } finally { File.Delete(outputFilePath); } Console.WriteLine("Original sequences are:"); sequences.ForEach(Console.WriteLine); Console.WriteLine("Benchmark sequences are:"); orgSequences.ForEach(Console.WriteLine); // Begin alignment PAMSAMMultipleSequenceAligner.FasterVersion = false; PAMSAMMultipleSequenceAligner.UseWeights = false; PAMSAMMultipleSequenceAligner.UseStageB = true; PAMSAMMultipleSequenceAligner.NumberOfCores = 2; int gapOpenPenalty = -13; int gapExtendPenalty = -5; int kmerLength = 3; int numberOfDegrees = 2; int numberOfPartitions = 16; SimilarityMatrix similarityMatrix = new SimilarityMatrix(SimilarityMatrix.StandardSimilarityMatrix.Blosum62); DistanceFunctionTypes distanceFunctionName = DistanceFunctionTypes.EuclideanDistance; UpdateDistanceMethodsTypes hierarchicalClusteringMethodName = UpdateDistanceMethodsTypes.Average; ProfileAlignerNames profileAlignerName = ProfileAlignerNames.NeedlemanWunschProfileAligner; ProfileScoreFunctionNames profileProfileFunctionName = ProfileScoreFunctionNames.WeightedInnerProduct; PAMSAMMultipleSequenceAligner msa = new PAMSAMMultipleSequenceAligner (sequences, kmerLength, distanceFunctionName, hierarchicalClusteringMethodName, profileAlignerName, profileProfileFunctionName, similarityMatrix, gapOpenPenalty, gapExtendPenalty, numberOfPartitions, numberOfDegrees); Console.WriteLine("Benchmark SPS score is: {0}", MsaUtils.MultipleAlignmentScoreFunction(orgSequences, similarityMatrix, gapOpenPenalty, gapExtendPenalty)); Console.WriteLine("Aligned sequences in stage 1: {0}", msa.AlignmentScoreA); for (int i = 0; i < msa.AlignedSequencesA.Count; ++i) { Console.WriteLine(msa.AlignedSequencesA[i]); } Console.WriteLine("Alignment score Q is: {0}", MsaUtils.CalculateAlignmentScoreQ(msa.AlignedSequencesA, orgSequences)); Console.WriteLine("Alignment score TC is: {0}", MsaUtils.CalculateAlignmentScoreTC(msa.AlignedSequencesA, orgSequences)); Console.WriteLine("Aligned sequences in stage 2: {0}", msa.AlignmentScoreB); for (int i = 0; i < msa.AlignedSequencesB.Count; ++i) { Console.WriteLine(msa.AlignedSequencesB[i]); } Console.WriteLine("Alignment score Q is: {0}", MsaUtils.CalculateAlignmentScoreQ(msa.AlignedSequencesB, orgSequences)); Console.WriteLine("Alignment score TC is: {0}", MsaUtils.CalculateAlignmentScoreTC(msa.AlignedSequencesB, orgSequences)); Console.WriteLine("Aligned sequences in stage 3: {0}", msa.AlignmentScoreC); for (int i = 0; i < msa.AlignedSequencesC.Count; ++i) { Console.WriteLine(msa.AlignedSequencesC[i]); } Console.WriteLine("Alignment score Q is: {0}", MsaUtils.CalculateAlignmentScoreQ(msa.AlignedSequencesC, orgSequences)); Console.WriteLine("Alignment score TC is: {0}", MsaUtils.CalculateAlignmentScoreTC(msa.AlignedSequencesC, orgSequences)); Console.WriteLine("Aligned sequences final: {0}", msa.AlignmentScore); for (int i = 0; i < msa.AlignedSequences.Count; ++i) { Console.WriteLine(msa.AlignedSequences[i]); } Console.WriteLine("Alignment score Q is: {0}", MsaUtils.CalculateAlignmentScoreQ(msa.AlignedSequences, orgSequences)); Console.WriteLine("Alignment score TC is: {0}", MsaUtils.CalculateAlignmentScoreTC(msa.AlignedSequences, orgSequences)); }