Scalable and Robust Dimension Reduction and Clustering

Scalable and Robust Dimension Reduction and Clustering
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This project focuses on developing a method called DACIDR for scalable dimension reduction and clustering of large-scale bioinformatics data. The methodology involves deterministic annealing clustering and interpolative dimension reduction techniques, along with visualization methods such as PlotViz3 for cluster identification in 3D. The project aims to enable faster observation and verification of genomic data through efficient data processing and visualization strategies.

  • Dimension Reduction
  • Clustering
  • Bioinformatics
  • Visualization
  • Scalability
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Uploaded on Feb 28, 2025 | 0 Views

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  1. SCALABLE AND ROBUST DIMENSION REDUCTION AND CLUSTERING Yang Ruan Advised by Geoffrey Fox

  2. Motivation Bioinformatics Data Deluge Large Scale Data Clustering Large Scale Date Visualization Enable Faster Observation and Verification <- id <- Sequence >SRR042318.5 GAGTTTAGCCTTGCG >SRR042318.32 GAGTTTAGCCTTGCG >SRR042318.70 GAGTTTTAGCCTTGCGG >SRR042318.81 GTTTAGCCTTGC DACIDR

  3. Overview of DACIDR Deterministic Annealing Clustering and Interpolative Dimension Reduction Method (DACIDR) Split input set into in-samples and out-of-samples Apply full pairwise clustering and multidimensional scaling on in- samples Use in-sample result to interpolate out-of-samples. Pairwise Clustering All-Pair Sequence Alignment Visualization Interpolation Multidimensional Scaling Simplified Flow Chart of DACIDR

  4. Clustering Visualization Use PlotViz3 to visualize the result in 3D Different identified cluster on in different color DACIDR is parallelized using Twister and MPI Metagenomics hmp16SrRNA COG Protein

  5. Phylogenetic Tree Visualization Spherical Phylogram visualized using the phylogenetic tree generated by RaXml using the representative sequences and reference sequences, the color scheme is same as in left figure. RaXml result visualized as Rectangular Phylogram shown in 2D

  6. Flowchart of the Process to Generate Spherical Phylogram

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