A look at Genome Assembly Visualization with ABySS-Explorer, as well as complementing genome browsing (Using clustering and interactive data exploration)

1. British Columbia Cancer Agency Genome Sciences Centre Vancouver . British Columbia . Canada Complementing Computation with Visualization in Genomics March 11, 2010 EBI Interfaces Interest Forum Cydney Nielsen

2. Discovery path Biological Sample Genomic Data Scientific Insight

3. Discovery path Biological Sample Genomic Data Scientific Insight

4. Components of Data Analysis Automation Analysis Genomic Data Scientific Insight Human Judgment

5. Outline Genome Assembly Visualization ABySS-Explorer Complement to genome browsing Using clustering and interactive data exploration

6. Outline Genome Assembly Visualization ABySS-Explorer Complement to genome browsing Using clustering and interactive data exploration

7. Genome Sequencing cell population extracted DNA Shotgun approach sheared DNA sequencing reads AGCGGATTGCATGACAGT GTACAGCCTGACAGAAGC GCGCTACGATCAGATCAA CATGACAGTCCGAGTACA TTCAGAATGGTACAGCAG

8. ABySS – Assembly ByShort Sequences Simpson et al. Genome Res 2009 Sequencing read set (read length = 7 nt): GGACATC GGACAGA Corresponding de Bruijn graph (k = 5 nt):

9. ABySS – Assembly ByShort Sequences Simpson et al. Genome Res 2009 Sequencing read set (read length = 7 nt): GGACATC GGACAGA Corresponding de Bruijn graph (k = 5 nt): ABySS merges unambiguously connected vertices to form contigs

10. Assembly Ambiguities True genome sequence GGATTGAAAAAAAAAAAAAAAAGTAGCACGAATATACATAGAAAAAAAAAAAAAAAAATTACG

11. Assembly Ambiguities True genome sequence GGATTGAAAAAAAAAAAAAAAAGTAGCACGAATATACATAGAAAAAAAAAAAAAAAAATTACG Assembled sequence de Bruijn graph representation

12. Starting Point Shaun Jackman

13. Example of existing tools: Consed

14. Example of existing tools: Consed

18. Properties of DNA

19. Capture sequence strand AAAAAT 2+ 1+

20. Capture sequence strand AAAAAT 2+ 1+ TTTTTA 2- 1-

21. Capture sequence strand AAAAAT 1+ 2+ TTTTTA

22. Capture sequence strand AAAAAT 1- 2- TTTTTA

24. Capture sequence length one oscillation = 100 nt

25. Genome Sequencing cell population extracted DNA read pair information read sheared DNA dsDNA fragment (known size) sequencing reads (typically produce millions) AGCGGATTGCATGACAGT read GTACAGCCTGACAGAAGC GCGCTACGATCAGATCAA CATGACAGTCCGAGTACA TTCAGAATGGTACAGCAG

26. Capture read pair information After building the initial single-end (SE) contigs from k-mer sequences, ABySS uses paired-end reads to resolve ambiguities.

27. Capture read pair information Paired end read information is used the construct paired end (PE) contigs … 13+ 44- 46+ 4+ 79+ 70+ … blue gradient = paired end contig orange = selected single end contig

29. contig adjacency information

30. contig strand

31. contig length

32. paired-end relationships

33. paired-end contigs

34. Implemented using the Java Universal Network/Graph Framework (JUNG)

35. Applied the Kamada-Kawai layout algorithm (JUNG implementation)

37. http://www.bcgsc.ca/platform/bioinfo/software/abyss-explorer

39. This representation is particularly powerful for revealing high-level genome assembly structure, not readily viewable in any other interactive tool

40. Future work includes:

41. support for other assembly algorithm outputs

42. enable flexible annotation display

44. Genome Sequencing cell population extracted DNA sheared DNA sequencing reads (typically produce millions) AGCGGATTGCATGACAGT GTACAGCCTGACAGAAGC GCGCTACGATCAGATCAA CATGACAGTCCGAGTACA TTCAGAATGGTACAGCAG

45. Genome Sequencing cell population extracted DNA sheared DNA sequencing reads (typically produce millions) AGCGGATTGCATGACAGT GTACAGCCTGACAGAAGC GCGCTACGATCAGATCAA CATGACAGTCCGAGTACA TTCAGAATGGTACAGCAG

46. Genome Sequencing cell population Chromatin Immunoprecipitationand Sequencing (ChIP-Seq) extracted DNA selection sheared DNA sequencing reads (typically produce millions) AGCGGATTGCATGACAGT GTACAGCCTGACAGAAGC GCGCTACGATCAGATCAA GTACAGCCTGACAGAAGC CATGACAGTCCGAGTACA TTCAGAATGGTACAGCAG TTCAGAATGGTACAGCAG

47. Align sequences to the genome CCGAGTACAGCCTGACAGA GCATGACAGTCCGAGTAC TTGCATGACAGTCCGAGT AGCGGATTGCATGACAGT AGCGGATTGCATGACAGT AGCGGATTGCATGACAGT Reference Genome AGCGGATTGCATGACAGTCCGAGTACAGCCTGACAGA Read coverage Genomic coordinate

48. Genome browser can reveal local patterns H3K4me3 H3K36me3 H3K27me3 H3K9me3 H3K9Ac MRE

49. Difficult to get global overview

50. Focus on regions of interest 1. For example, transcriptional start sites (TSS +/- 3000 nt) H3K4me3 H3K9Ac H3K4me1 H3K36me3 MeDIP MRE 2. Extract data matrices Normalization for bin i, sample h: 3. Cluster matrices (k-means clustering with Euclidean distance)

51. Focus on regions of interest 1. For example, transcriptional start sites (TSS +/- 3000 nt) H3K4me3 H3K9Ac H3K4me1 H3K36me3 MeDIP MRE 2. Extract data matrices Normalization for bin i, sample h: 3. Cluster matrices (k-means clustering with Euclidean distance)

52. Focus on regions of interest 1. For example, transcriptional start sites (TSS +/- 3000 nt) H3K4me3 H3K9Ac H3K4me1 H3K36me3 MeDIP MRE 2. Extract data matrices Normalization for bin i, sample h: 3. Cluster matrices (k-means clustering with Euclidean distance)

53. Enable interactive exploration 4. Interactive cluster visualization (data from H1 cells) cluster size indicator (total n= 15,618) H3K4me3 H3K9Ac H3K4me1 H3K36me3 H3K27me3 H3K9me3 MeDIP MRE mRNA H3K4me3 H3K9Ac H3K4me1 H3K36me3 H3K27me3 H3K9me3 MeDIP MRE mRNA cluster (average values displayed) individual TSS H3K4me3 H3K9Ac H3K4me1 H3K36me3 H3K27me3 H3K9me3 MeDIP MRE mRNA HOXC12 gene scroll bar to explore all cluster members 5. Link-out to UCSC genome browser

54. Enable interactive exploration 4. Interactive cluster visualization (data from H1 cells) cluster size indicator (total n= 15,618) H3K4me3 H3K9Ac H3K4me1 H3K36me3 H3K27me3 H3K9me3 MeDIP MRE mRNA H3K4me3 H3K9Ac H3K4me1 H3K36me3 H3K27me3 H3K9me3 MeDIP MRE mRNA cluster (average values displayed) individual TSS H3K4me3 H3K9Ac H3K4me1 H3K36me3 H3K27me3 H3K9me3 MeDIP MRE mRNA scroll bar to explore all cluster members

55. Enable interactive exploration 4. Interactive cluster visualization (data from H1 cells) cluster size indicator (total n= 15,618) H3K4me3 H3K9Ac H3K4me1 H3K36me3 H3K27me3 H3K9me3 MeDIP MRE mRNA H3K4me3 H3K9Ac H3K4me1 H3K36me3 H3K27me3 H3K9me3 MeDIP MRE mRNA cluster (average values displayed) individual TSS H3K4me3 H3K9Ac H3K4me1 H3K36me3 H3K27me3 H3K9me3 MeDIP MRE mRNA HOXC12 gene scroll bar to explore all cluster members 5. Link-out to UCSC genome browser

58. Access to both global and detailed view is valuable

59. Future work includes:

60. search functionality (e.g. by region id)

61. integration with other clustering tools

65. Complementing Computation with Visualization in Genomics March 11, 2010 Cydney Nielsen BC Cancer Agency Genome Sciences Centre Vancouver, Canada