sept2016 sv dnanexus_benchmarking
TRANSCRIPT
The Global Network For Genomics™
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Mix and Match:Assessing Structural Variation Calling with Varying Coverages and AlgorithmsAndrew CarrollHead of Science, DNAnexus
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Global Cloud-based Platform Secure, Scalable, and Collaborative
solution for Genomics
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Overview of Structural Variation
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Calling with short reads is challenging
Alkan, Coe, and Eichler (2011)
• Difficult for reads to span events
• Mapping is hard in low complexity regions
• GC Bias• Rely on other
signals –• Insert size• Clipping• Read
orientation
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Short-Read Structural Variant Tools
xDELLY
xCREST
xPindel
xBreakDancer
xLUMPY
xCNVnator
xManta
xBreakseq2
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Calling SV with PacBio Data
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Tools for PacBio DataPB Honey Sniffles Parliament
Adam English
Fritz Sedlazeck
Adam English
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Apps
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Benchmarks – Part IOnly PacBio Data
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Creation of Multi-Technology Truth Set• SV Calls were contributed for a variety of
technologies (Illumina, PacBio, BioNano, 10X Genomics, Complete Genomics)
• Split confident call lists into deletions occurring in regions with tandem repeats and those not in regions with tandem repeats
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Recall – PBHoney and Sniffles - Deletions
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Complementarity at 10-Fold Coverage
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Benchmarks – Part IIIllumina + PacBio Data
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Parliament Pipeline
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Recall – Parliament (Assembly vs PacBio)
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Ensemble Strategies
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Call Overlap at 10-Fold Coverage
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Full Combination Ensemble Strategies
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Conclusions1. With Illumina data at 30-fold coverage, SV calling can
be effective at PacBio data coverages as low as 3–5 fold
2. More PacBio data coverage seems to be always better over investigated ranges (mostly thanks to PBHoney)
3. With only PacBio data, 10–15 fold gives good SV calling results with reasonable sequencing investment
4. Running both Sniffles and PBHoney gives best results, especially at lower (5–15 fold) PacBio data coverages
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Thank-you!Genome in a BottleJustin Zook
Baylor College of MedicineAdam EnglishWill Salerno
Schatz LabFritz Sedlazeck
DNAnexusAndrew CarrollSinger MaBrett HanniganYih-Chii HwangMarcus KinsellaAbhiram DasSamantha Zarate
