Jan2016 fritz sedlazeck mapping and sv calling from pac bio
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1. The workshop discussed improving structural variant detection from long read sequencing data, including better breakpoint prediction, genotyping assessment, and handling complex structural variants. 2. A new version of the Sniffles algorithm was presented that improves speed, accuracy, and false discovery rates for breakpoint prediction. 3. A limitation of using a single gap penalty cost for indel detection was discussed, as it does not properly model the different characteristics of sequencing errors versus real indels. A convex gap cost function was proposed to address this.
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Jan2016 fritz sedlazeck mapping and sv calling from pac bio
- 2. Previous meetings: Utilizing long reads 1. How to predict the breakpoints? 2. How to assess genotype ? 3. Complex SVs?
- 3. 1. Breakpoint prediction • Over BWA-MEM alignments – First version had a bug… • Redesigning Sniffles – Improved speed – Improved accuracy on noisy alignment – Improved read filtering -> reducing FDR – Optional realignment step • Improved breakpoint accuracy • Improving Genotyping
- 5. Sniffles v02
- 6. Current limitations • Linear: gap cost always the same • Affine: separate penalties for opening and extending a gap • Using one gap cost is considered state of the art • Problem with PacBio/ONT: two different gap models required – Sequencing error: large high number of 1 bp indels – Real indels: extending a gap more likely than opening a new one – Sequencing error + repeats cause one gap cost to fail even for real indels AAAGAATTCA A-A-A-T-CA AAAGAATTCA AAA----TCA vs.
- 7. Convex gap costs • Costs for a gap follow a convex function of gap length • Close to linear gap costs for 1 - 2 bp gaps • As gap gets longer penalty for "splitting" gaps increases • Problem optimal approach: O(nm2 + n2m) • Heuristic implementation O(nm)
- 9. NGM-LR reconcile Read within inversion Read within duplication
- 10. Deletion
- 11. Deletion
- 12. Insertions
- 13. Inversions
- 14. Translocations
- 16. Outlook • Finish new version of Sniffles – Assessment of noisy alignments • NGM-LR: – MQ calculation – Runtime • Visual inspection and comparison of SV calls
Editor's Notes
- Delete repeating regions + low score. LIS: Longest increasing subsequence. cLIS: Longes increasing subsequence + with respect on the location along the read. (let it run multiple times. Max rounds 10). Bei low quality region -> reconcile.