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HG-CoLoR: Hybrid Graph for the error Correction of Long Reads Pierre Morisse , Thierry Lecroq and Arnaud Lefebvre pierre.morisse2@univ-rouen.fr Laboratoire dInformatique, de Traitement de lInformation et des Syst` emes July 5, 2017

  1. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Inspiration NaS [Madoui et al., 2015] Does not locally correct erroneous regions Uses long reads as templates to generate corrected long reads from assemblies of short reads Requires the mapping of the short reads both on the long reads and against each other P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 8/30

  2. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion NaS overview NaS corrects a long read as follows: long read seeds P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 9/30

  3. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion NaS overview NaS corrects a long read as follows: seeds similar short reads P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 9/30

  4. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion NaS overview NaS corrects a long read as follows: P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 9/30

  5. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion NaS overview NaS corrects a long read as follows: contig P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 9/30

  6. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Main idea Generate corrected long reads from assemblies of short reads Get rid of the time consuming step of aligning the short reads against each other Focus on a seed and extend approach Rely on a hybrid structure between a de Bruijn graph and an overlap graph, built from the short reads P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 10/30

  7. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Main idea Generate corrected long reads from assemblies of short reads Get rid of the time consuming step of aligning the short reads against each other Focus on a seed and extend approach Rely on a hybrid structure between a de Bruijn graph and an overlap graph, built from the short reads P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 10/30

  8. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Main idea Generate corrected long reads from assemblies of short reads Get rid of the time consuming step of aligning the short reads against each other Focus on a seed and extend approach Rely on a hybrid structure between a de Bruijn graph and an overlap graph, built from the short reads P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 10/30

  9. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Introduction 1 2 Main idea Hybrid graph 3 Workflow 4 Experimental results 5 6 Conclusion P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 11/30

  10. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Hybrid graph Overlap graph de Bruijn graph 4 ATTGC TTGCG TGCGT ATTGCGT GCGTAAC ATAACGG 1 AACGG GCGTA ATAAC TAACG GTAAC CGTAA Idea Mix the advantages of a de Bruijn graph and of an overlap graph, and allow to compute overlaps of variable lengths between the k -mers from the reads of a given set. P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 12/30

  11. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Hybrid graph Overlap graph de Bruijn graph 4 ATTGC TTGCG TGCGT ATTGCGT GCGTAAC ATAACGG 1 AACGG GCGTA ATAAC TAACG GTAAC CGTAA Idea Mix the advantages of a de Bruijn graph and of an overlap graph, and allow to compute overlaps of variable lengths between the k -mers from the reads of a given set. P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 12/30

  12. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Hybrid graph Overlap graph de Bruijn graph 4 ATTGC TTGCG TGCGT ATTGCGT GCGTAAC ATAACGG 1 AACGG GCGTA ATAAC TAACG GTAAC CGTAA Idea Mix the advantages of a de Bruijn graph and of an overlap graph, and allow to compute overlaps of variable lengths between the k -mers from the reads of a given set. P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 12/30

  13. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Hybrid graph Overlap graph de Bruijn graph 4 ATTGC TTGCG TGCGT ATTGCGT GCGTAAC ATAACGG 1 AACGG GCGTA ATAAC TAACG GTAAC CGTAA Idea Mix the advantages of a de Bruijn graph and of an overlap graph, and allow to compute overlaps of variable lengths between the k -mers from the reads of a given set. P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 12/30

  14. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Hybrid graph Example On the set of reads S = { AAGCTTAG, CTTACGTA, GTATACTG } AAGCTT 4 5 5 3 AGCTTA GCTTAG 3 4 4 3 5 5 5 5 CTTACG TTACGT TACGTA GTATAC TATACT ATACTG 3 4 P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 13/30

  15. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Hybrid graph Example On the set of reads S = { AAGCTTAG, CTTACGTA, GTATACTG } AAGCTT 4 5 5 3 AGCTTA GCTTAG 3 4 4 3 5 5 5 5 CTTACG TTACGT TACGTA GTATAC TATACT ATACTG 3 4 P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 13/30

  16. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Hybrid graph Example On the set of reads S = { AAGCTTAG, CTTACGTA, GTATACTG } AAGCTT 4 5 5 3 AGCTTA GCTTAG 3 4 4 3 5 5 5 5 CTTACG TTACGT TACGTA GTATAC TATACT ATACTG 3 4 P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 13/30

  17. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Hybrid graph traversal The graph is not explicitly built Its traversal is simulated with PgSA [Kowalski et al., 2015] PgSA can index a set of reads and answer queries about strings of variable lengths One of the queries returns the positions of all the occurrences of a given string in the different reads P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 14/30

  18. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Hybrid graph traversal The graph is not explicitly built Its traversal is simulated with PgSA [Kowalski et al., 2015] PgSA can index a set of reads and answer queries about strings of variable lengths One of the queries returns the positions of all the occurrences of a given string in the different reads P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 14/30

  19. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Hybrid graph traversal The graph is not explicitly built Its traversal is simulated with PgSA [Kowalski et al., 2015] PgSA can index a set of reads and answer queries about strings of variable lengths One of the queries returns the positions of all the occurrences of a given string in the different reads P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 14/30

  20. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Hybrid graph traversal The graph is not explicitly built Its traversal is simulated with PgSA [Kowalski et al., 2015] PgSA can index a set of reads and answer queries about strings of variable lengths One of the queries returns the positions of all the occurrences of a given string in the different reads P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 14/30

  21. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Introduction 1 2 Main idea Hybrid graph 3 Workflow 4 Experimental results 5 6 Conclusion P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 15/30

  22. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Workflow 5 steps: Correct the short reads 1 Align the short reads on the long read, to find seeds 2 Merge the overlapping seeds 3 Link the seeds, by traversing the hybrid graph 4 Extend the obtained corrected long read, on the left (resp. right) 5 of the leftmost (resp. rightmost) seed P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 16/30

  23. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Workflow 5 steps: Correct the short reads 1 Align the short reads on the long read, to find seeds 2 Merge the overlapping seeds 3 Link the seeds, by traversing the hybrid graph 4 Extend the obtained corrected long read, on the left (resp. right) 5 of the leftmost (resp. rightmost) seed P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 16/30

  24. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Workflow 5 steps: Correct the short reads 1 Align the short reads on the long read, to find seeds 2 Merge the overlapping seeds 3 Link the seeds, by traversing the hybrid graph 4 Extend the obtained corrected long read, on the left (resp. right) 5 of the leftmost (resp. rightmost) seed P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 16/30

  25. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Workflow 5 steps: Correct the short reads 1 Align the short reads on the long read, to find seeds 2 Merge the overlapping seeds 3 Link the seeds, by traversing the hybrid graph 4 Extend the obtained corrected long read, on the left (resp. right) 5 of the leftmost (resp. rightmost) seed P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 16/30

  26. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Workflow 5 steps: Correct the short reads 1 Align the short reads on the long read, to find seeds 2 Merge the overlapping seeds 3 Link the seeds, by traversing the hybrid graph 4 Extend the obtained corrected long read, on the left (resp. right) 5 of the leftmost (resp. rightmost) seed P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 16/30

  27. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Step 4: Seeds linking Seeds are used as anchor points on the hybrid graph The graph is traversed to link together the seeds and assemble the k -mers P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 17/30

  28. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Step 4: Seeds linking Seeds are used as anchor points on the hybrid graph The graph is traversed to link together the seeds and assemble the k -mers P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 17/30

  29. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Step 4: Seeds linking long read seed 1 seed 2 seed 3 k − 1 k − 2 . . . k − 1 . . . k − 2 k − 1 . . . k − 1 . . . src dst k − 3 . . . k − 2 k − 3 . . . P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 18/30

  30. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Step 4: Seeds linking long read src dst seed 3 k − 1 k − 2 . . . k − 1 . . . k − 2 k − 1 . . . k − 1 . . . src dst k − 3 . . . k − 2 k − 3 . . . P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 18/30

  31. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Step 4: Seeds linking long read src dst seed 3 k − 1 k − 2 . . . k − 1 . . . k − 2 k − 1 . . . k − 1 . . . src dst k − 3 . . . k − 2 k − 3 . . . P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 18/30

  32. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Step 4: Seeds linking long read src dst seed 3 k − 1 k − 2 . . . k − 1 . . . k − 2 k − 1 . . . k − 1 . . . src src dst k − 3 . . . k − 2 k − 3 . . . P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 18/30

  33. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Step 4: Seeds linking long read src dst seed 3 k − 1 k − 2 . . . k − 1 . . . k − 2 k − 1 . . . k − 1 . . . src src dst k − 3 . . . k − 2 k − 3 . . . P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 18/30

  34. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Step 4: Seeds linking long read src dst seed 3 k − 1 k − 2 . . . k − 1 . . . k − 2 k − 1 . . . k − 1 . . . src dst k − 3 . . . k − 2 k − 3 . . . P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 18/30

  35. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Step 4: Seeds linking long read src dst seed 3 k − 1 k − 2 . . . k − 1 . . . k − 2 k − 1 . . . k − 1 . . . src dst k − 3 . . . k − 2 k − 3 . . . P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 18/30

  36. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Step 4: Seeds linking long read src dst seed 3 k − 1 k − 2 . . . k − 1 . . . k − 2 k − 1 . . . k − 1 . . . src dst k − 3 k − 2 . . . k − 3 . . . P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 18/30

  37. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Step 4: Seeds linking long read src dst seed 3 k − 1 k − 2 . . . k − 1 . . . k − 2 k − 1 . . . k − 1 . . . src dst k − 3 . . . k − 2 k − 3 . . . P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 18/30

  38. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Step 4: Seeds linking long read src dst seed 3 k − 1 k − 2 . . . k − 1 . . . k − 2 k − 1 . . . k − 1 . . . src dst k − 3 . . . k − 2 k − 3 . . . P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 18/30

  39. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Step 4: Seeds linking long read src dst seed 3 k − 1 k − 2 . . . . . . k − 1 . . . k − 2 k − 1 . . . k − 1 . . . src dst k − 3 . . . k − 2 k − 3 . . . P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 18/30

  40. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Step 4: Seeds linking long read src dst seed 3 k − 1 k − 2 . . . k − 1 . . . k − 2 k − 1 . . . k − 1 . . . src src dst k − 3 . . . k − 2 k − 3 . . . P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 18/30

  41. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Step 4: Seeds linking long read src dst seed 3 k − 1 k − 2 . . . k − 1 . . . k − 2 k − 1 . . . k − 1 . . . src src dst k − 3 . . . k − 2 k − 3 . . . P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 18/30

  42. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Step 4: Seeds linking long read src dst seed 3 k − 1 k − 2 . . . k − 1 . . . k − 2 k − 1 . . . k − 1 . . . src dst k − 3 . . . k − 2 k − 3 . . . P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 18/30

  43. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Step 4: Seeds linking long read src dst seed 3 k − 1 k − 2 . . . k − 1 . . . k − 2 k − 1 . . . k − 1 . . . src dst k − 3 . . . k − 2 k − 3 . . . P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 18/30

  44. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Step 4: Seeds linking long read src dst seed 3 k − 1 k − 2 . . . k − 1 . . . k − 2 k − 1 . . . . . . k − 1 . . . src dst k − 3 . . . k − 2 k − 3 . . . P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 18/30

  45. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Step 4: Seeds linking long read src dst seed 3 k − 1 k − 2 . . . k − 1 . . . k − 2 k − 1 . . . . . . k − 1 . . . src dst k − 3 . . . k − 2 k − 3 . . . P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 18/30

  46. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Step 4: Seeds linking long read src dst seed 3 k − 1 k − 2 . . . k − 1 . . . k − 2 k − 1 . . . k − 1 . . . src dst dst k − 3 . . . k − 2 k − 3 . . . P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 18/30

  47. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Step 4: Seeds linking long read src dst seed 3 k − 1 k − 2 . . . k − 1 . . . k − 2 k − 1 . . . . . . k − 1 . . . src src dst dst k − 3 . . . k − 2 k − 3 . . . P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 18/30

  48. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Step 4: Seeds linking long read linked seeds seed 3 k − 1 k − 2 . . . k − 1 . . . . . . . . . src dst k − 3 . . . k − 2 k − 3 . . . P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 18/30

  49. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Step 4: Seeds linking long read src dst k − 1 k − 2 . . . k − 1 . . . . . . . . . src dst k − 3 k − 2 . . . k − 3 . . . P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 18/30

  50. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Step 4: Seeds linking long read corrected long read k − 1 k − 2 . . . k − 1 . . . . . . . . . src dst k − 3 k − 2 . . . k − 3 . . . P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 18/30

  51. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Step 5: Tips extension Seeds don’t always map right at the beginning or until the end of the long read Once all the seeds have been linked, HG-CoLoR keeps on traversing the graph The traversal stops when the borders of the long read or a branching path are reached P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 19/30

  52. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Step 5: Tips extension Seeds don’t always map right at the beginning or until the end of the long read Once all the seeds have been linked, HG-CoLoR keeps on traversing the graph The traversal stops when the borders of the long read or a branching path are reached P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 19/30

  53. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Step 5: Tips extension Seeds don’t always map right at the beginning or until the end of the long read Once all the seeds have been linked, HG-CoLoR keeps on traversing the graph The traversal stops when the borders of the long read or a branching path are reached P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 19/30

  54. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Remark Some seeds might be impossible to link together ⇒ Production of a corrected long read fragmented in multiple parts P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 20/30

  55. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Remark Some seeds might be impossible to link together ⇒ Production of a corrected long read fragmented in multiple parts P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 20/30

  56. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Introduction 1 2 Main idea Hybrid graph 3 Workflow 4 Experimental results 5 6 Conclusion P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 21/30

  57. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Datasets HG-CoLoR was compared to NaS, and two other state-of-the-art long read hybrid correction methods: CoLoRMap [Haghshenas et al., 2016] and Jabba [Miclotte et al., 2016] The different tools were compared on the following datasets Reference genome Oxford Nanopore data Illumina data Dataset Name Strain Genome size # Reads Average length Coverage # Reads Read length Coverage E. coli E. coli K-12 substr. MG1655 4.6 Mbp 22,270 5,999 28x 775,500 300 50x Yeast S. cerevisae W303 12.4 Mbp 205,923 5,698 31x 2,500,000 250 50x P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 22/30

  58. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Alignment-based comparison Dataset Method # Reads Average length Average identity Genome coverage Runtime Original 22,270 5,999 79.46% 100% N/A CoLoRMap 22,270 6,219 89.02% 100% 8h26min E. coli Jabba 22,065 5,794 99.81% 99.41% 12min56 NaS 21,818 7,926 99.86% 100% 3 days HG-CoLoR 22,549 5,897 99.59% 100% 3h Original 205,923 5,698 55.49% 99.90% N/A CoLoRMap 205,923 5,737 39.93% 99.40% 37h36min Yeast Jabba 36,958 6,613 99.55% 93.21% 44min05 NaS 71,793 5,938 99.59% 98.70% > 16 days HG-CoLoR 71,518 6,604 99.17% 98.39% 22h P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 23/30

  59. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Alignment-based comparison Dataset Method # Reads Average length Average identity Genome coverage Runtime Original 22,270 5,999 79.46% 100% N/A CoLoRMap 22,270 6,219 89.02% 100% 8h26min E. coli Jabba 22,065 5,794 99.81% 99.41% 12min56 NaS 21,818 7,926 99.86% 100% 3 days HG-CoLoR 22,549 5,897 99.59% 100% 3h Original 205,923 5,698 55.49% 99.90% N/A CoLoRMap 205,923 5,737 39.93% 99.40% 37h36min Yeast Jabba 36,958 6,613 99.55% 93.21% 44min05 NaS 71,793 5,938 99.59% 98.70% > 16 days HG-CoLoR 71,518 6,604 99.17% 98.39% 22h P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 23/30

  60. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Alignment-based comparison Dataset Method # Reads Average length Average identity Genome coverage Runtime Original 22,270 5,999 79.46% 100% N/A CoLoRMap 22,270 6,219 89.02% 100% 8h26min E. coli Jabba 22,065 5,794 99.81% 99.41% 12min56 NaS 21,818 7,926 99.86% 100% 3 days HG-CoLoR 22,549 5,897 99.59% 100% 3h Original 205,923 5,698 55.49% 99.90% N/A CoLoRMap 205,923 5,737 39.93% 99.40% 37h36min Yeast Jabba 36,958 6,613 99.55% 93.21% 44min05 NaS 71,793 5,938 99.59% 98.70% > 16 days HG-CoLoR 71,518 6,604 99.17% 98.39% 22h P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 23/30

  61. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Alignment-based comparison Dataset Method # Reads Average length Average identity Genome coverage Runtime Original 22,270 5,999 79.46% 100% N/A CoLoRMap 22,270 6,219 89.02% 100% 8h26min E. coli Jabba 22,065 5,794 99.81% 99.41% 12min56 NaS 21,818 7,926 99.86% 100% 3 days HG-CoLoR 22,549 5,897 99.59% 100% 3h Original 205,923 5,698 55.49% 99.90% N/A CoLoRMap 205,923 5,737 39.93% 99.40% 37h36min Yeast Jabba 36,958 6,613 99.55% 93.21% 44min05 NaS 71,793 5,938 99.59% 98.70% > 16 days HG-CoLoR 71,518 6,604 99.17% 98.39% 22h P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 23/30

  62. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Alignment-based comparison Dataset Method # Reads Average length Average identity Genome coverage Runtime Original 22,270 5,999 79.46% 100% N/A CoLoRMap 22,270 6,219 89.02% 100% 8h26min E. coli Jabba 22,065 5,794 99.81% 99.41% 12min56 NaS 21,818 7,926 99.86% 100% 3 days HG-CoLoR 22,549 5,897 99.59% 100% 3h Original 205,923 5,698 55.49% 99.90% N/A CoLoRMap 205,923 5,737 39.93% 99.40% 37h36min Yeast Jabba 36,958 6,613 99.55% 93.21% 44min05 NaS 71,793 5,938 99.59% 98.70% > 16 days HG-CoLoR 71,518 6,604 99.17% 98.39% 22h P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 23/30

  63. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Assembly-based comparison Dataset Method Coverage # Expected contigs # Obtained contigs Genome coverage Identity CoLoRMap 28x 1 29 97,74% 99.81% Jabba 28x 1 41 95.76% 99.92% E. coli NaS 37x 1 1 99.90% 99.99% HG-CoLoR 29x 1 2 99.95% 99.95% CoLoRMap 14x 30 Jabba 21x 30 134 70.52% 99.83% Yeast NaS 35x 30 123 97.44% 99.77% HG-CoLoR 39x 30 108 92.19% 99.61% P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 24/30

  64. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Assembly-based comparison Dataset Method Coverage # Expected contigs # Obtained contigs Genome coverage Identity CoLoRMap 28x 1 29 97,74% 99.81% Jabba 28x 1 41 95.76% 99.92% E. coli NaS 37x 1 1 99.90% 99.99% HG-CoLoR 29x 1 2 99.95% 99.95% CoLoRMap 14x 30 Jabba 21x 30 134 70.52% 99.83% Yeast NaS 35x 30 123 97.44% 99.77% HG-CoLoR 39x 30 108 92.19% 99.61% P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 24/30

  65. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Assembly-based comparison Dataset Method Coverage # Expected contigs # Obtained contigs Genome coverage Identity CoLoRMap 28x 1 29 97,74% 99.81% Jabba 28x 1 41 95.76% 99.92% E. coli NaS 37x 1 1 99.90% 99.99% HG-CoLoR 29x 1 2 99.95% 99.95% CoLoRMap 14x 30 Jabba 21x 30 134 70.52% 99.83% Yeast NaS 35x 30 123 97.44% 99.77% HG-CoLoR 39x 30 108 92.19% 99.61% P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 24/30

  66. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Assembly-based comparison Dataset Method Coverage # Expected contigs # Obtained contigs Genome coverage Identity CoLoRMap 28x 1 29 97,74% 99.81% Jabba 28x 1 41 95.76% 99.92% E. coli NaS 37x 1 1 99.90% 99.99% HG-CoLoR 29x 1 2 99.95% 99.95% CoLoRMap 14x 30 Jabba 21x 30 134 70.52% 99.83% Yeast NaS 35x 30 123 97.44% 99.77% HG-CoLoR 39x 30 108 92.19% 99.61% P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 24/30

  67. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Assembly-based comparison Dataset Method Coverage # Expected contigs # Obtained contigs Genome coverage Identity CoLoRMap 28x 1 29 97,74% 99.81% Jabba 28x 1 41 95.76% 99.92% E. coli NaS 37x 1 1 99.90% 99.99% HG-CoLoR 29x 1 2 99.95% 99.95% CoLoRMap 14x 30 Jabba 21x 30 134 70.52% 99.83% Yeast NaS 35x 30 123 97.44% 99.77% HG-CoLoR 39x 30 108 92.19% 99.61% P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 24/30

  68. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Introduction 1 2 Main idea Hybrid graph 3 Workflow 4 Experimental results 5 6 Conclusion P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 25/30

  69. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Conclusion We introduced a new graph structure and proved its usefulness We developed a new hybrid long read error correction method We showed that this new method provides the best trade off between runtime, accuracy and genome coverage, when compared to state-of-the-art methods HG-CoLoR is available from: https://github.com/pierre-morisse/HG-CoLoR P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 26/30

  70. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Conclusion We introduced a new graph structure and proved its usefulness We developed a new hybrid long read error correction method We showed that this new method provides the best trade off between runtime, accuracy and genome coverage, when compared to state-of-the-art methods HG-CoLoR is available from: https://github.com/pierre-morisse/HG-CoLoR P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 26/30

  71. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Conclusion We introduced a new graph structure and proved its usefulness We developed a new hybrid long read error correction method We showed that this new method provides the best trade off between runtime, accuracy and genome coverage, when compared to state-of-the-art methods HG-CoLoR is available from: https://github.com/pierre-morisse/HG-CoLoR P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 26/30

  72. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Conclusion We introduced a new graph structure and proved its usefulness We developed a new hybrid long read error correction method We showed that this new method provides the best trade off between runtime, accuracy and genome coverage, when compared to state-of-the-art methods HG-CoLoR is available from: https://github.com/pierre-morisse/HG-CoLoR P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 26/30

  73. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Future work Run HG-CoLoR on larger genomes Filter out weak k -mers after the short reads correction step Build a proper assembly tool from the hybrid graph structure Adapt HG-CoLoR to self-correction P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 27/30

  74. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Future work Run HG-CoLoR on larger genomes Filter out weak k -mers after the short reads correction step Build a proper assembly tool from the hybrid graph structure Adapt HG-CoLoR to self-correction P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 27/30

  75. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Future work Run HG-CoLoR on larger genomes Filter out weak k -mers after the short reads correction step Build a proper assembly tool from the hybrid graph structure Adapt HG-CoLoR to self-correction P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 27/30

  76. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Future work Run HG-CoLoR on larger genomes Filter out weak k -mers after the short reads correction step Build a proper assembly tool from the hybrid graph structure Adapt HG-CoLoR to self-correction P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 27/30

  77. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion References I Haghshenas, E., Hach, F., Sahinalp, S. C., and Chauve, C. (2016). CoLoRMap: Correcting Long Reads by Mapping short reads. Bioinformatics , 32(17):i545–i551. Kowalski, T., Grabowski, S., and Deorowicz, S. (2015). Indexing arbitrary-length k-mers in sequencing reads. PLoS ONE , 10(7):1–14. Madoui, M.-A., Engelen, S., Cruaud, C., Belser, C., Bertrand, L., Alberti, A., Lemainque, A., Wincker, P ., and Aury, J.-M. (2015). Genome assembly using Nanopore-guided long and error-free DNA reads. BMC Genomics , 16:327. P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 28/30

  78. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion References II Miclotte, G., Heydari, M., Demeester, P ., Rombauts, S., Van de Peer, Y., Audenaert, P ., and Fostier, J. (2016). Jabba: hybrid error correction for long sequencing reads. Algorithms Mol Biol , 11:10. P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 29/30

  79. Introduction Main idea Hybrid graph Workflow Experimental results Conclusion Questions? P. Morisse, T. Lecroq, A. Lefebvre HG-CoLoR 30/30

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