コード例 #1
0
 public HomeController(IParserManager parserManager,
                       IHierarchicalClustering hierarchicalClustering,
                       IClusterSerializer clusterSerializer)
 {
     ParserManager          = parserManager;
     HierarchicalClustering = hierarchicalClustering;
     ClusterSerializer      = clusterSerializer;
 }
コード例 #2
0
 /// <summary>
 /// Construct a tree by hierarchical clustering method.
 ///
 /// The node list is already generated in the hierarchical clustering method
 /// and the root will be the last node in the list
 /// </summary>
 /// <param name="hCluster">hierarcical clustering class object</param>
 public BinaryGuideTree(IHierarchicalClustering hCluster)
 {
     if (hCluster == null)
     {
         throw new ArgumentException("null Hierarchical clustering class");
     }
     if (hCluster.Nodes.Count == 0)
     {
         throw new ArgumentException("empty node list in Hierarchical clustering class");
     }
     _nodes          = hCluster.Nodes;
     _edges          = hCluster.Edges;
     _root           = hCluster.Nodes[hCluster.Nodes.Count - 1];
     _numberOfNodes  = hCluster.Nodes.Count;
     _numberOfLeaves = (_numberOfNodes + 2) / 2;
 }
コード例 #3
0
        /// <summary>
        /// Performs Stage 1, 2, and 3 as described in class description.
        /// </summary>
        /// <param name="inputSequences"></param>
        /// <returns></returns>
        public IList <Bio.Algorithms.Alignment.ISequenceAlignment> Align(IEnumerable <ISequence> inputSequences)
        {
            List <ISequence> sequences = inputSequences.ToList();

            // Initializations
            if (sequences.Count > 0)
            {
                if (ConsensusResolver == null)
                {
                    ConsensusResolver = new SimpleConsensusResolver(_alphabet);
                }
                else
                {
                    ConsensusResolver.SequenceAlphabet = _alphabet;
                }
            }

            // Get ProfileAligner ready
            IProfileAligner profileAligner = null;

            switch (_profileAlignerName)
            {
            case (ProfileAlignerNames.NeedlemanWunschProfileAligner):
                if (_degreeOfParallelism == 1)
                {
                    profileAligner = new NeedlemanWunschProfileAlignerSerial(
                        SimilarityMatrix, _profileProfileFunctionName, GapOpenCost, GapExtensionCost, _numberOfPartitions);
                }
                else
                {
                    profileAligner = new NeedlemanWunschProfileAlignerParallel(
                        SimilarityMatrix, _profileProfileFunctionName, GapOpenCost, GapExtensionCost, _numberOfPartitions);
                }
                break;

            case (ProfileAlignerNames.SmithWatermanProfileAligner):
                if (_degreeOfParallelism == 1)
                {
                    profileAligner = new SmithWatermanProfileAlignerSerial(
                        SimilarityMatrix, _profileProfileFunctionName, GapOpenCost, GapExtensionCost, _numberOfPartitions);
                }
                else
                {
                    profileAligner = new SmithWatermanProfileAlignerParallel(
                        SimilarityMatrix, _profileProfileFunctionName, GapOpenCost, GapExtensionCost, _numberOfPartitions);
                }
                break;

            default:
                throw new ArgumentException("Invalid profile aligner name");
            }

            _alignedSequences = new List <ISequence>(sequences.Count);
            float currentScore = 0;

            // STAGE 1

            Performance.Snapshot("Stage 1");
            // Generate DistanceMatrix
            KmerDistanceMatrixGenerator kmerDistanceMatrixGenerator =
                new KmerDistanceMatrixGenerator(sequences, _kmerLength, _alphabet, _distanceFunctionName);

            // Hierarchical clustering
            IHierarchicalClustering hierarcicalClustering =
                new HierarchicalClusteringParallel
                    (kmerDistanceMatrixGenerator.DistanceMatrix, _hierarchicalClusteringMethodName);

            // Generate Guide Tree
            BinaryGuideTree binaryGuideTree =
                new BinaryGuideTree(hierarcicalClustering);

            // Progressive Alignment
            IProgressiveAligner progressiveAlignerA = new ProgressiveAligner(profileAligner);

            progressiveAlignerA.Align(sequences, binaryGuideTree);

            currentScore = MsaUtils.MultipleAlignmentScoreFunction(progressiveAlignerA.AlignedSequences, SimilarityMatrix, GapOpenCost, GapExtensionCost);
            if (currentScore > _alignmentScoreA)
            {
                _alignmentScoreA   = currentScore;
                _alignedSequencesA = progressiveAlignerA.AlignedSequences;
            }
            if (_alignmentScoreA > _alignmentScore)
            {
                _alignmentScore   = _alignmentScoreA;
                _alignedSequences = _alignedSequencesA;
            }

            if (PAMSAMMultipleSequenceAligner.FasterVersion)
            {
                _alignedSequencesB = _alignedSequencesA;
                _alignedSequencesC = _alignedSequencesA;
                _alignmentScoreB   = _alignmentScoreA;
                _alignmentScoreC   = _alignmentScoreA;
            }
            else
            {
                BinaryGuideTree               binaryGuideTreeB              = null;
                IHierarchicalClustering       hierarcicalClusteringB        = null;
                KimuraDistanceMatrixGenerator kimuraDistanceMatrixGenerator = new KimuraDistanceMatrixGenerator();

                if (PAMSAMMultipleSequenceAligner.UseStageB)
                {
                    // STAGE 2
                    Performance.Snapshot("Stage 2");
                    // Generate DistanceMatrix from Multiple Sequence Alignment

                    int iterateTime = 0;

                    while (true)
                    {
                        ++iterateTime;
                        kimuraDistanceMatrixGenerator.GenerateDistanceMatrix(_alignedSequences);

                        // Hierarchical clustering
                        hierarcicalClusteringB = new HierarchicalClusteringParallel
                                                     (kimuraDistanceMatrixGenerator.DistanceMatrix, _hierarchicalClusteringMethodName);

                        // Generate Guide Tree
                        binaryGuideTreeB = new BinaryGuideTree(hierarcicalClusteringB);

                        BinaryGuideTree.CompareTwoTrees(binaryGuideTreeB, binaryGuideTree);
                        binaryGuideTree = binaryGuideTreeB;

                        // Progressive Alignment
                        IProgressiveAligner progressiveAlignerB = new ProgressiveAligner(profileAligner);
                        progressiveAlignerB.Align(sequences, binaryGuideTreeB);

                        currentScore = MsaUtils.MultipleAlignmentScoreFunction(progressiveAlignerB.AlignedSequences, SimilarityMatrix, GapOpenCost, GapExtensionCost);

                        if (currentScore > _alignmentScoreB)
                        {
                            _alignmentScoreB   = currentScore;
                            _alignedSequencesB = progressiveAlignerB.AlignedSequences;
                            break;
                        }
                        else
                        {
                            break;
                        }
                    }
                    if (_alignmentScoreB > _alignmentScore)
                    {
                        _alignmentScore   = _alignmentScoreB;
                        _alignedSequences = _alignedSequencesB;
                    }
                }
                else
                {
                    binaryGuideTreeB = binaryGuideTree;
                }


                // STAGE 3
                Performance.Snapshot("Stage 3");
                // refinement
                //int maxRefineMentTime = sequences.Count * 2 - 2;
                int maxRefineMentTime = 1;
                if (sequences.Count == 2)
                {
                    maxRefineMentTime = 0;
                }

                int refinementTime = 0;
                _alignedSequencesC = new List <ISequence>(sequences.Count);
                for (int i = 0; i < sequences.Count; ++i)
                {
                    _alignedSequencesC.Add(
                        new Sequence(Alphabets.GetAmbiguousAlphabet(_alphabet),
                                     _alignedSequences[i].ToArray())
                    {
                        ID       = _alignedSequences[i].ID,
                        Metadata = _alignedSequences[i].Metadata
                    });
                }

                List <int>[]        leafNodeIndices            = null;
                List <int>[]        allIndelPositions          = null;
                IProfileAlignment[] separatedProfileAlignments = null;
                List <int>[]        eStrings = null;

                while (refinementTime < maxRefineMentTime)
                {
                    ++refinementTime;
                    Performance.Snapshot("Refinement iter " + refinementTime.ToString());
                    bool needRefinement = false;
                    for (int edgeIndex = 0; edgeIndex < binaryGuideTreeB.NumberOfEdges; ++edgeIndex)
                    {
                        leafNodeIndices = binaryGuideTreeB.SeparateSequencesByCuttingTree(edgeIndex);

                        allIndelPositions = new List <int> [2];

                        separatedProfileAlignments = ProfileAlignment.ProfileExtraction(_alignedSequencesC, leafNodeIndices[0], leafNodeIndices[1], out allIndelPositions);
                        eStrings = new List <int> [2];

                        if (separatedProfileAlignments[0].NumberOfSequences < separatedProfileAlignments[1].NumberOfSequences)
                        {
                            profileAligner.Align(separatedProfileAlignments[0], separatedProfileAlignments[1]);
                            eStrings[0] = profileAligner.GenerateEString(profileAligner.AlignedA);
                            eStrings[1] = profileAligner.GenerateEString(profileAligner.AlignedB);
                        }
                        else
                        {
                            profileAligner.Align(separatedProfileAlignments[1], separatedProfileAlignments[0]);
                            eStrings[0] = profileAligner.GenerateEString(profileAligner.AlignedB);
                            eStrings[1] = profileAligner.GenerateEString(profileAligner.AlignedA);
                        }

                        for (int set = 0; set < 2; ++set)
                        {
                            Parallel.ForEach(leafNodeIndices[set], PAMSAMMultipleSequenceAligner.parallelOption, i =>
                            {
                                //Sequence seq = new Sequence(_alphabet, "");
                                List <byte> seqBytes = new List <byte>();

                                int indexAllIndel = 0;
                                for (int j = 0; j < _alignedSequencesC[i].Count; ++j)
                                {
                                    if (indexAllIndel < allIndelPositions[set].Count && j == allIndelPositions[set][indexAllIndel])
                                    {
                                        ++indexAllIndel;
                                    }
                                    else
                                    {
                                        seqBytes.Add(_alignedSequencesC[i][j]);
                                    }
                                }

                                _alignedSequencesC[i]    = profileAligner.GenerateSequenceFromEString(eStrings[set], new Sequence(Alphabets.GetAmbiguousAlphabet(_alphabet), seqBytes.ToArray()));
                                _alignedSequencesC[i].ID = _alignedSequencesC[i].ID;
                                (_alignedSequencesC[i] as Sequence).Metadata = _alignedSequencesC[i].Metadata;
                            });
                        }

                        currentScore = MsaUtils.MultipleAlignmentScoreFunction(_alignedSequencesC, SimilarityMatrix, GapOpenCost, GapExtensionCost);

                        if (currentScore > _alignmentScoreC)
                        {
                            _alignmentScoreC = currentScore;
                            needRefinement   = true;

                            // recreate the tree
                            kimuraDistanceMatrixGenerator.GenerateDistanceMatrix(_alignedSequencesC);
                            hierarcicalClusteringB = new HierarchicalClusteringParallel
                                                         (kimuraDistanceMatrixGenerator.DistanceMatrix, _hierarchicalClusteringMethodName);

                            binaryGuideTreeB = new BinaryGuideTree(hierarcicalClusteringB);
                            break;
                        }
                    }
                    if (!needRefinement)
                    {
                        refinementTime = maxRefineMentTime;
                        break;
                    }
                }
                if (_alignmentScoreC > _alignmentScore)
                {
                    _alignmentScore   = _alignmentScoreC;
                    _alignedSequences = _alignedSequencesC;
                }
                Performance.Snapshot("Stop Stage 3");
            }

            //just for the purpose of integrating PW and MSA with the same output
            IList <Bio.Algorithms.Alignment.ISequenceAlignment> results = new List <Bio.Algorithms.Alignment.ISequenceAlignment>();

            return(results);
        }
コード例 #4
0
        /// <summary>
        /// Performs Stage 1, 2, and 3 as described in class description.
        /// </summary>
        /// <param name="sequences">Input sequences</param>
        /// <returns>Alignment results</returns>
        private void DoAlignment(IList <ISequence> sequences)
        {
            Debug.Assert(this.alphabet != null);
            Debug.Assert(sequences.Count > 0);

            // Initializations
            if (ConsensusResolver == null)
            {
                ConsensusResolver = new SimpleConsensusResolver(this.alphabet);
            }
            else
            {
                ConsensusResolver.SequenceAlphabet = this.alphabet;
            }

            // Get ProfileAligner ready
            IProfileAligner profileAligner = null;

            switch (ProfileAlignerName)
            {
            case (ProfileAlignerNames.NeedlemanWunschProfileAligner):
                if (this.degreeOfParallelism == 1)
                {
                    profileAligner = new NeedlemanWunschProfileAlignerSerial(
                        SimilarityMatrix, ProfileProfileFunctionName, GapOpenCost, GapExtensionCost, this.numberOfPartitions);
                }
                else
                {
                    profileAligner = new NeedlemanWunschProfileAlignerParallel(
                        SimilarityMatrix, ProfileProfileFunctionName, GapOpenCost, GapExtensionCost, this.numberOfPartitions);
                }
                break;

            case (ProfileAlignerNames.SmithWatermanProfileAligner):
                if (this.degreeOfParallelism == 1)
                {
                    profileAligner = new SmithWatermanProfileAlignerSerial(
                        SimilarityMatrix, ProfileProfileFunctionName, GapOpenCost, GapExtensionCost, this.numberOfPartitions);
                }
                else
                {
                    profileAligner = new SmithWatermanProfileAlignerParallel(
                        SimilarityMatrix, ProfileProfileFunctionName, GapOpenCost, GapExtensionCost, this.numberOfPartitions);
                }
                break;

            default:
                throw new ArgumentException("Invalid profile aligner name");
            }

            this.AlignedSequences = new List <ISequence>(sequences.Count);
            float currentScore = 0;

            // STAGE 1

            ReportLog("Stage 1");
            // Generate DistanceMatrix
            var kmerDistanceMatrixGenerator = new KmerDistanceMatrixGenerator(sequences, KmerLength, this.alphabet, DistanceFunctionName);

            // Hierarchical clustering
            IHierarchicalClustering hierarcicalClustering =
                new HierarchicalClusteringParallel
                    (kmerDistanceMatrixGenerator.DistanceMatrix, HierarchicalClusteringMethodName);

            // Generate Guide Tree
            var binaryGuideTree = new BinaryGuideTree(hierarcicalClustering);

            // Progressive Alignment
            IProgressiveAligner progressiveAlignerA = new ProgressiveAligner(profileAligner);

            progressiveAlignerA.Align(sequences, binaryGuideTree);

            currentScore = MsaUtils.MultipleAlignmentScoreFunction(progressiveAlignerA.AlignedSequences, SimilarityMatrix, GapOpenCost, GapExtensionCost);
            if (currentScore > this.AlignmentScoreA)
            {
                this.AlignmentScoreA   = currentScore;
                this.AlignedSequencesA = progressiveAlignerA.AlignedSequences;
            }
            if (this.AlignmentScoreA > this.AlignmentScore)
            {
                this.AlignmentScore   = this.AlignmentScoreA;
                this.AlignedSequences = this.AlignedSequencesA;
            }

            if (PAMSAMMultipleSequenceAligner.FasterVersion)
            {
                this.AlignedSequencesB = this.AlignedSequencesA;
                this.AlignedSequencesC = this.AlignedSequencesA;
                this.AlignmentScoreB   = this.AlignmentScoreA;
                this.AlignmentScoreC   = this.AlignmentScoreA;
            }
            else
            {
                BinaryGuideTree               binaryGuideTreeB              = null;
                IHierarchicalClustering       hierarcicalClusteringB        = null;
                KimuraDistanceMatrixGenerator kimuraDistanceMatrixGenerator = new KimuraDistanceMatrixGenerator();

                if (UseStageB)
                {
                    // STAGE 2
                    ReportLog("Stage 2");
                    // Generate DistanceMatrix from Multiple Sequence Alignment

                    while (true)
                    {
                        kimuraDistanceMatrixGenerator.GenerateDistanceMatrix(this.AlignedSequences);

                        // Hierarchical clustering
                        hierarcicalClusteringB = new HierarchicalClusteringParallel
                                                     (kimuraDistanceMatrixGenerator.DistanceMatrix, HierarchicalClusteringMethodName);

                        // Generate Guide Tree
                        binaryGuideTreeB = new BinaryGuideTree(hierarcicalClusteringB);

                        BinaryGuideTree.CompareTwoTrees(binaryGuideTreeB, binaryGuideTree);
                        binaryGuideTree = binaryGuideTreeB;

                        // Progressive Alignment
                        IProgressiveAligner progressiveAlignerB = new ProgressiveAligner(profileAligner);
                        progressiveAlignerB.Align(sequences, binaryGuideTreeB);

                        currentScore = MsaUtils.MultipleAlignmentScoreFunction(progressiveAlignerB.AlignedSequences, SimilarityMatrix, GapOpenCost, GapExtensionCost);

                        if (currentScore > this.AlignmentScoreB)
                        {
                            this.AlignmentScoreB   = currentScore;
                            this.AlignedSequencesB = progressiveAlignerB.AlignedSequences;
                        }
                        break;
                    }
                    if (this.AlignmentScoreB > this.AlignmentScore)
                    {
                        this.AlignmentScore   = this.AlignmentScoreB;
                        this.AlignedSequences = this.AlignedSequencesB;
                    }
                }
                else
                {
                    binaryGuideTreeB = binaryGuideTree;
                }


                // STAGE 3
                ReportLog("Stage 3");
                // refinement
                int maxRefineMentTime = 1;
                if (sequences.Count == 2)
                {
                    maxRefineMentTime = 0;
                }

                int refinementTime = 0;
                this.AlignedSequencesC = new List <ISequence>(this.AlignedSequences.Count);
                foreach (ISequence t in this.AlignedSequences)
                {
                    this.AlignedSequencesC.Add(new Sequence(Alphabets.GetAmbiguousAlphabet(this.alphabet), t.ToArray())
                    {
                        ID = t.ID,
                        // Do not shallow copy dictionary
                        //Metadata = t.Metadata
                    });
                }

                while (refinementTime < maxRefineMentTime)
                {
                    ++refinementTime;
                    ReportLog("Refinement iter " + refinementTime);
                    bool needRefinement = false;
                    for (int edgeIndex = 0; edgeIndex < binaryGuideTreeB.NumberOfEdges; ++edgeIndex)
                    {
                        List <int>[] leafNodeIndices = binaryGuideTreeB.SeparateSequencesByCuttingTree(edgeIndex);

                        List <int>[] allIndelPositions = new List <int> [2];

                        IProfileAlignment[] separatedProfileAlignments = ProfileAlignment.ProfileExtraction(this.AlignedSequencesC, leafNodeIndices[0], leafNodeIndices[1], out allIndelPositions);
                        List <int>[]        eStrings = new List <int> [2];

                        if (separatedProfileAlignments[0].NumberOfSequences < separatedProfileAlignments[1].NumberOfSequences)
                        {
                            profileAligner.Align(separatedProfileAlignments[0], separatedProfileAlignments[1]);
                            eStrings[0] = profileAligner.GenerateEString(profileAligner.AlignedA);
                            eStrings[1] = profileAligner.GenerateEString(profileAligner.AlignedB);
                        }
                        else
                        {
                            profileAligner.Align(separatedProfileAlignments[1], separatedProfileAlignments[0]);
                            eStrings[0] = profileAligner.GenerateEString(profileAligner.AlignedB);
                            eStrings[1] = profileAligner.GenerateEString(profileAligner.AlignedA);
                        }

                        for (int set = 0; set < 2; ++set)
                        {
                            Parallel.ForEach(leafNodeIndices[set], ParallelOption, i =>
                            {
                                //Sequence seq = new Sequence(_alphabet, "");
                                List <byte> seqBytes = new List <byte>();

                                int indexAllIndel = 0;
                                for (int j = 0; j < this.AlignedSequencesC[i].Count; ++j)
                                {
                                    if (indexAllIndel < allIndelPositions[set].Count && j == allIndelPositions[set][indexAllIndel])
                                    {
                                        ++indexAllIndel;
                                    }
                                    else
                                    {
                                        seqBytes.Add(this.AlignedSequencesC[i][j]);
                                    }
                                }

                                this.AlignedSequencesC[i]    = profileAligner.GenerateSequenceFromEString(eStrings[set], new Sequence(Alphabets.GetAmbiguousAlphabet(this.alphabet), seqBytes.ToArray()));
                                this.AlignedSequencesC[i].ID = this.AlignedSequencesC[i].ID;
                                // Do not shallow copy dictionary
                                //(_alignedSequencesC[i] as Sequence).Metadata = _alignedSequencesC[i].Metadata;
                            });
                        }

                        currentScore = MsaUtils.MultipleAlignmentScoreFunction(this.AlignedSequencesC, SimilarityMatrix, GapOpenCost, GapExtensionCost);

                        if (currentScore > this.AlignmentScoreC)
                        {
                            this.AlignmentScoreC = currentScore;
                            needRefinement       = true;

                            // recreate the tree
                            kimuraDistanceMatrixGenerator.GenerateDistanceMatrix(this.AlignedSequencesC);
                            hierarcicalClusteringB = new HierarchicalClusteringParallel
                                                         (kimuraDistanceMatrixGenerator.DistanceMatrix, HierarchicalClusteringMethodName);

                            binaryGuideTreeB = new BinaryGuideTree(hierarcicalClusteringB);
                            break;
                        }
                    }
                    if (!needRefinement)
                    {
                        refinementTime = maxRefineMentTime;
                        break;
                    }
                }
                if (this.AlignmentScoreC > this.AlignmentScore)
                {
                    this.AlignmentScore   = this.AlignmentScoreC;
                    this.AlignedSequences = this.AlignedSequencesC;
                }
                ReportLog("Stop Stage 3");
            }
        }
コード例 #5
0
ファイル: PamSamBvtTestCases.cs プロジェクト: cpatmoore/bio
        /// <summary>
        ///     Get the binary tree object using hierarchical clustering object
        /// </summary>
        /// <param name="hierarchicalClustering">hierarchical Clustering</param>
        /// <returns>Binary guide tree</returns>
        private static BinaryGuideTree GetBinaryTree(IHierarchicalClustering hierarchicalClustering)
        {
            // Generate Guide Tree
            var binaryGuideTree =
                new BinaryGuideTree(hierarchicalClustering);

            return binaryGuideTree;
        }
コード例 #6
0
ファイル: BinaryGuideTree.cs プロジェクト: cpatmoore/bio
 /// <summary>
 /// Construct a tree by hierarchical clustering method.
 /// 
 /// The node list is already generated in the hierarchical clustering method
 /// and the root will be the last node in the list
 /// </summary>
 /// <param name="hCluster">hierarcical clustering class object</param>
 public BinaryGuideTree(IHierarchicalClustering hCluster)
 {
     if (hCluster == null)
     {
         throw new ArgumentException("null Hierarchical clustering class");
     }
     if (hCluster.Nodes.Count == 0)
     {
         throw new ArgumentException("empty node list in Hierarchical clustering class");
     }
     _nodes = hCluster.Nodes;
     _edges = hCluster.Edges;
     _root = hCluster.Nodes[hCluster.Nodes.Count - 1];
     _numberOfNodes = hCluster.Nodes.Count;
     _numberOfLeaves = (_numberOfNodes + 2) / 2;
 }