Sept2016 sv illumina

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A Population-Based SV Callset Michael Eberle September 15, 2016

COMPANY CONFIDENTIAL – FOR INTERNAL USE ONLY

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Populations as a CNV/SV discovery tool

●  Collected high-depth WGS data from 3,000-4,000 samples

●  Current SV & CNV callers and SNP information can be used for hypothesis generation -  Manta, Canvas & SNP GT information (HWE)

●  Confirm CNVs and SVs and refine break points -  Combination of depth and assembly

●  Create targeted callers for common SVs -  Develop improved methods to call these variants on any sample

(improved consistency and accuracy)


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Hypothesis generation

●  Manta (split read) calls from ~3,000 samples -  Good for deletions up to ~10kb -  These variants should work well for graph-based calling

●  Canvas (depth) calls from ~3,000 samples -  Primarily deletions >10kb -  These variants should be callable using targeted depth analysis

●  Population genetics (SNP calls from ~2,200 Europeans) -  Good for most size ranges but relies on SNPs overlapping CNV -  May identify variants that split read methods miss


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Small SV Validation and boundary resolution


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Assembly of putative deletions

●  Assemble common deletions using different methods -  K-mer approach (SPAdes) -  String assembly (SGA)

●  Large number of samples should improve assembly -  5% deletion ~ 4,500x depth (in 3,000 sequenced samples) -  Easy if we can identify just the reads associated with the deletion -  Low complexity (e.g. STRs) and variability around break-ends are

problematic (but highlight issues that need to be resolved)

●  Assembled ~9,800 deletions to break point resolution -  Starting from Manta calls in PG and population


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Genotyping deletions with graphs

●  Graph alignment + genotyping tool -  Create a sequence graph for deletions -  Align + count reads on BP edges and

on BP boundaries

●  “Genotype” deletions via mixture model on read counts.

●  Very preliminary results and some obvious improvements are still in progress

REF+ALT REF+ALT

REF REF BP end REF BP start

ALT BP 25 BP up

25 BP down 25 BP up

25 BP down

Candidate events in Platinum Genomes:


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PG Pedigree Genotyping

●  High-level variant statistics

-  ~3,700 hom-ref, 830 hom-alt -  ~1,100 variants consistent -  ~2,000 variants probably wrong in

<= 2 samples -  ~1,900 need improvement


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Giab Trio Analysis

●  GIAB Ashkenazim Trio: -  HG002 – Son -  HG003 – Father -  HG004 – Mother

●  Trio Statistics (Total: 9,739) Outcome Count Percentage

Homref everywhere 3,425 35.2%

Pass 2,131 21.9%

Conflict (5) / Male X is het (28) 33 0.3%

Parents het 1,045 10.7%

Called in 2 1,637 16.8%

Called in <= 1 1,468 15.1%


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Depth-based validation and boundary resolution


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Canvas-identified deletion in the population

●  Characterization of a high frequency call

●  Use fine-grained depth-map to isolate boundaries of the call


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Improving breakpoints – depth pileup

●  Characterization of a high frequency call

●  Use fine-grained depth-map to isolate boundaries of the call

1 kb

1 kb


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Improving breakpoints – six double deletions

180 bp

180 bp

•  Assembly from 6 hom del samples resolves breakpoints and co-inserted sequence •  Expect ~5 double deletions in 3,000 samples for deletions with ~4% frequency


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Next steps (for deletions)

●  Complete merging of all the putative common deletions -  Currently some parts of this work are proceeding in parallel and we

have not merged the analysis/variants yet

●  Attempt to validate and refine all deletions -  LD, depth, assembly

●  Finish graph-based GT and depth-based GT -  QC these GT callers using both Mendel errors and HWE

●  Map calls onto PG and GIAB samples

●  Demonstrate other variants on other samples -  Sequencing 150 Coriell samples of diverse ethnicity to provide

additional support of calls within (and outside of) GIAB families


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Acknowledgements

Mitch Bekritsky (SNP analysis)

Andy Gross (population depth)

Nathan Johnson (assembly)

Peter Krusche (graph genotyping)

Sept2016 sv illumina

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