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Analysis of CDC June 2008 Data Using Distance Metrics

Visualizing CDC June 2008 data with Hamming and Euclidean distance metrics to cluster samples based on spoligotypes, Miru, CDC, and SpolDB3 families. Explore relationships between CDC families, Mycobacterium strains, and distance measures.

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Analysis of CDC June 2008 Data Using Distance Metrics

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  1. Visualization of CDC June 2008 data using various distance metrics

  2. Distance metrics • Hamming Distance between spoligotypes • Euclidean Distance between Miru

  3. Hamming Distance between Spoligotypes

  4. Euclidean Distance between Miru

  5. Euclidean Distance between Miru

  6. CDC June 2008 data • 9337 samples • Each sample has spoligotype, miru, CDC family, SpolDB3 family. • We clustered the data using Hidden Parent Assumption and Euclidean distance between Mirus to determine distance between samples.

  7. CDC June 2008 data – CDC families

  8. CDC June 2008 data – CDC families Indo-Oceanic East-African Indian Euro-American Mycobacterium bovis East Asian Mycobacterium africanum

  9. CDC families – East Asian

  10. CDC families – East-African Indian

  11. CDC families – Euro-American

  12. CDC families – Indo-Oceanic

  13. CDC families – Mycobacterium Africanum

  14. CDC families – Mycobacterium Bovis

  15. Zoom into the graph

  16. CDC June 2008 data – CDC families - Reminder

  17. CDC June 2008 data - SPOLDB3 families

  18. Miru Distance vs. Hamming Distance for all connectors(edges)

  19. Miru Distance vs. Hamming Distance for single-linked connectors(edges)

  20. Hamming Distance vs. Number of Sample Pairs for all connectors(edges) Miru Distance = 0

  21. Hamming Distance vs. Number of Sample Pairs for single-linked connectors(edges) with Miru Distance = 0

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