1. Jin Zhang, Jiayin Wang and Yufeng Wu
An improved approach for accurate and efficient calling of structural variations with low-coverage sequence data
Jin Zhang, Jiayin Wang and Yufeng Wu
Department of Computer Science and Engineering
University of Connecticut
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RECOMB-seq 2012

2. Structural Variation (SV)
Alternative
deletion
insertion
Reference
Reference
Alternative
Mean insert size + 3 σ
SV calling using HTS sequencing data
Method
Pair
or Single
Coverage
Exact
breakpoints
Assembly
Higher
Read depth No
Read pair
Pair only
Split read
Reference
Alternative
Deletion
Reference
Alternative
Deletion
Exact breakpoint
Mills et al. (Nature, 2011)
“…,which facilitated analysing their origin and functional impact.“
Lam et al. (Nature Biotechnology 2010)
classification and annotation
Problem
Finding SVs with Exact breakpoints using Low-coverage Paired-end reads
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RECOMB-seq 2012

3. Split-read mapping (e.g. Deletion)
Reads mapping tools:
Not map it
Or Soft-clipping
Focal region
Reference
Maximum event size
Alternative
Deletion
Because of sequence and repeats,
longer Maximum Event size (e.g. 1Mbps) may cause false positives
Different way of splits may cause even more false positives
Shorter maximum event size may reduce false positives
but also may fail to find some larger deletions
Method
Algorithm
Max Deletion Size
Cutoff
Insert Size
Focal Region
Pindel: Ye et al. (Bioinformatics 2009)
Pattern growth
Yes
SVseq1: Zhang et al. (Bioinformatics 2011)
BWT
SVseq2 (For this work)
(Recomb-seq 2012)
Dynamic Programming
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RECOMB-seq 2012
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RECOMB-seq 2012 3

4. SVseq2: a pattern for deletion calling:
Finding focal region with the help of a spanning pair
li: library mean
σ: standard deviation
l: read length
li + 3σ
Known breakpoint
Alternative
unknown breakpoint
li+ 3σ -2l
They are the same breakpoint on Alternative
Spanning pair
E.g. li+ 3σ -2l = *
= 350 bps
Note Maximum Event Size can be
1Mbps
Reference
li+ 3σ -2l
li+ 3σ -2l
Alternative
(not known)
Deletion
(a) within length li+ 3σ -2l from
,find
(b) Find by using , coz they are a pair
(c) Find by mapping the soft-clipped portion
within length li+ 3σ -2l of
Using focal region:
(1)Search in much smaller space
(2)Reduce the way of splits
(3)Able to find large deletions
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RECOMB-seq 2012

5. SVseq2: another pattern in deletion calling
Reference
Alternative
Deletion
Anchor
li+ 3σ -2l
The pair itself is also a spanning pair
Dynamic alignment algorithm (semi-global)
Similarity : 1 for matches and −1 for mismatches.
Penalty: for gaps inside the sequence, 0 outside.
GTTCTAAGCCAGTGGTTCTACCAACTTGAGTATGCATCAGAATCACTTGGA
AGTGGTTCT- CCAACTTGAGAATGCATCA
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RECOMB-seq 2012

6. SVseq2: Type III pattern for Insertion calling:
Read 1
Read 2
Alternative
Overlap
Region 1
Reference
Portion 3
Portion 2
Portion 1
Portion 4
Mapping score:
Penalties same as the deletion case
Calling:
Score / length of overlap < Threshold
SVseq2 currently not reconstruct inserted sequences
still use cutoff
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RECOMB-seq 2012

7. Results Simulation on deletions
Simulate on chromosome 15 (100, 338, 915 bps);
Introduce deletions with exact break from 1000 genomes project release:
union deletions.genotypes.vcf.gz (number of them are 132)
45 individuals
Simulate reads with wgsim ( (error rate 0.02)
Pair-ends reads with length 100, outer distance 500 Mapped by BWA
Cutoff: SVseq2: cutoff 3; SVseq1 cutoff 3; Pindel 0.2.4d cutoff 3
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RECOMB-seq 2012

8. Real data Individual data Pooled data
Illumina datasets of 18 individuals on chromosome 20 (9 CEU, 9YRI)
Mapped by BWA on NCBI37
Benchmark: ftp://ftp-trace.ncbi.nih.gov/1000genomes/ftp/technical/working/
Contains called SVs using BreakDancerMax1.1, CNVnator, GenomeStrip,
EMBL/Delly and Pindel ( with data of 1094 individuals)
SVseq2 Cutoff 3(no cutoff for type I) and 4; SVseq1 and Pindel 0.2.4d cutoff 3.
Individual data
Pooled data
** F: Findings SE: supported by Exact breakpoint SO: supported by Overlap
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RECOMB-seq 2012

9. Running time Acknowledgement NA19312, One Thread
Supported by NSF grant IIS
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RECOMB-seq 2012