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Canadian Bioinformatics Workshops

Canadian Bioinformatics Workshops. www.bioinformatics.ca. Module #: Title of Module. 2. Module 5 Visual Analysis of HT-seq data. Marc Fiume Informatics for High Throughput Sequencing Data June 9-10, 2014. Part II (continued): Visualizing Structural Variants.

samuelharrison
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Canadian Bioinformatics Workshops

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  1. Canadian Bioinformatics Workshops www.bioinformatics.ca

  2. Module #: Title of Module 2

  3. Module 5Visual Analysis of HT-seq data Marc Fiume Informatics for High Throughput Sequencing Data June 9-10, 2014

  4. Part II (continued): Visualizing Structural Variants

  5. Review: structural variation detection • covered in Module 4 • two complementary approaches: • depth of coverage (DOC) • paired end mapping (PEM)

  6. PEM: small insertions donor reference

  7. PEM: large insertions donor reference

  8. PEM: deletions donor reference

  9. PEM: inversions donor reference one read inverted when mapped

  10. PEM: tandem duplications donor reference order of read mappings reversed

  11. Structural Variation Visualization in IGV

  12. Structural Variants in Savant • Savant has a visualization mode for BAM files called “Matepair (Arc)” that is specialized for identifying structural variants using the PEM methodology • it connects the locations of paired mappings by an arc • arc height represents the mapped distance • arc color represents the relative orientation of the reads (for complex rearrangements, like inverstions)

  13. Structural Variation Visualization in Savant

  14. Lab Time

  15. Quiz (but not really)

  16. Question 1 which visualization mode in Savant is best for finding SNPs? why?

  17. Question 2 which visualization mode in Savant is best for finding structural variations? why?

  18. Question 3 what kind of event does this image depict? e.g. chr1: 5,195,017 - 5,199,144

  19. A: INSERTION donor reference

  20. Question 4 what kind of event does this image depict? chr1: 26,489,321 - 26,490,661

  21. A: DELETION donor reference

  22. Question 5 what would a heterozygous deletion look like? chr1: 31,574,172 - 31,578,242

  23. Question 6 what kind of event does this image depict? chr1: 81,659,802 - 81,661,916

  24. A: Inversion donor reference one read inverted when mapped

  25. Question 7 what kind of event does this image depict? chr1: 11,050,416 - 11,055,457

  26. A: Tandem Duplication donor reference order of read mappings reversed

  27. Part III : Interactive Variant Analysis this is bonus material, covered if time permits contact mfiume@cs.toronto.edu for questions

  28. Genetic Variant Analysis • finding disease-causing genetic mutation is “like trying to find a needle in a haystack needlestack” • lots of variants • many distractors • many false positives • errors in sequencing • errors in variant prediction • most true positives are not causal • not related to phenotype of interest, not damaging

  29. Genetic Variant Analysis • filter variants based on quality, effect, and relevance to disease variant calling annotation filtration visualization Modules 1-3 Module 4.1

  30. Existing Tools • command-line is powerful but not interactive • Excel / Genome Browsers are interactive but not powerful

  31. chr1 : 102,435,394 – 129,485,349 GO

  32. MedSavant, a variant search engine

  33. MedSavant • visual analytics from variant calling to disease mutation discovery variant calling annotation filtration visualization MedSavant

  34. You might also want to try • VarSifter works in memory, good for small projects • this space is evolving; difficult to do a comprehensive comparison • much more commercial activity compared to genome browsers VarSifter Golden Helix SVS (commercial)

  35. Lab Time

  36. We are on a Coffee Break & Networking Session

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