Aug2013 real time genomics trio pedigree analysis

© 2013 Real Time Genomics, Inc.

NA12878 Trio/Pedigree Analysis

Francisco M. De La Vega, D.Sc. VP Genome Science


Leveraging trio information •  GiaB has selected reference materials in the form of father,

mother, offspring trios •  The goal was to leverage the Mendelian inheritance patterns

to: –  Identify variant genotype errors that are inconsistent with

Mendelian inheritance –  Remove these errors from the reference baseline calls

•  However, if variant identification methods don't use directly pedigree information and jointly analyze the trio alignments, an opportunity to improve the genotype calls would be missed

•  We focused on using the RTG Family caller to better leverage the shared information in the trios and improve the call set, whilst reducing Mendelian inconsistent genotype errors


C A A

A A A A A A

A

A A

A

A A /Genotype:

A A

C A

C

C A A

A A

A /Genotype: C

C

A /Genotype:

A C

C

C

|

||

Variant calling can be improved by jointly analyzing related samples

Shared haplotypes


C A A

A A A A A A

A

A A

A

A A /Genotype:

A A

C A

C

C A A

A A

A /Genotype: C

C

A /Genotype:

A C

C

C

|

||

Variant calling can be improved by jointly analyzing related samples

Mendelian variant segregaJon

Shared haplotypes


Mendelian inconsistency

C

C

/Genotype: C

C

C

C C

C C

A A A

A A /Genotype: (Low QV)

C A

A

A A

A

A /Genotype:

C

C

C A

A A

C C

A C

|

||


Joint trio analysis corrects Mendelian errors

C

/Genotype: C

C

C

C

C T

G

G

G

C T C T

C T

C A

A

A A

A

Genotype:

C

A / C

G

G G G G G

G A A A

Genotype: (Good QV)

C T C T C T C T

A / C

G G G A A

C C

A C

|

||


NA12878 calls from trio calling

•  Comparing offspring variants from singleton vs pedigree calling –  Both showing good quality metrics

•  Using family information more good calls can be made and dubious calls are downgraded

NA12878 Call set SNVs Indels MNPs

SNV Het/Hom Ti/Tv

% dbSNP (r129)

RTG single 3,329,797 558,242 31,070 1.55 2.11 90.8%

RTG trio 3,363,619 595,030 33,686 1.57 2.11 90.4%

GATK/VQSR 3,263,289 610,837 N/A 1.51 2.09 91.7%

Variant StaBsBcs

Data: WGS 2x100bp >50X Illumina PlaJnum Genomes data (ENA Acc. No. ERP001960). RTG AVR score cut-‐off 0.15; GATK v1.7 & BWA 0.6.1.

142,848

68,000

Family

Singleton

3,849,457

NA12878

NA12891 NA12892


NA12878 vs reference datasets

NA12878 Call set

1kP OMNI Poly (TP%)

1kP OMNI Mono (FP%)

Get-‐RM¶

(TP %) GiaB (TP%)

GiaB-‐BED (TP%)

RTG single 97.5% 0.10% 97.4% N/A N/A

RTG trio 97.5% 0.24% 97.0% 90.5% 94.1%

GATK/VQSR 97.8% 0.17% 87.8% 88.4% 92.5%

§ RelaJve to dbSNP 137; StaJsJcs for SNVs only. ¶Get-‐RM consistent high-‐quality variants; n=498

NA12878

NA12891 NA12892

–  1000 Genomes Illumina OMNI SNP array •  Polymorphic sites – TP proxy •  Monomorphic sites – FP proxy

–  Get-RM high confidence call set –  GiaB high confidence calls in BED region


ROC Trio calls vs. GiAB baseline (BED)

RTG snpsimeval tool; SNV/indel/MNP; zygosity match


ROC Trio calls vs. GiaB baseline



ROC Trio calls vs. CGI baseline



Mendelian inconsistency errors

RTG family caller reduces Mendelian Inheritance Errors over 60X vs. RTG singleton calling (over 70X vs. GATK/VQSR)

Log Co

unts of M

IE

1

10

100

1000

10000

100000

1000000

RTG single RTG trio GATK/VQSR

335,625

4,870

351,904


Pattern #1: Heterozygous variant

Trio Calling

NA12878

NA12892NA12891

NA12877

NA12889 NA12890

NA12879 NA12880 NA12881 NA12882 NA12883 NA12884 NA12885 NA12886 NA12887 NA12888 NA12893

0/1

0/10/0

0/0 0/0 0/00/0 0/00/1 0/1 0/10/10/1


Segregation of heterozygous variants

0

20,000

40,000

60,000

80,000

1 2 3 4 5 6 7 8 9 10 11

SNV coun

t

# of offspring segregaBng

SNV

0

100

200

300

400

500

1 2 3 4 5 6 7 8 9 10 11

MNP coun

t


MNP

0

2,000

4,000

6,000

8,000

10,000

1 2 3 4 5 6 7 8 9 10 11

inde

l coun

t


indel

0

20,000

40,000

60,000

80,000

100,000

1 2 3 4 5 6 7 8 9 10 11

Varia

nt cou

nt

# of offspirng segregaBng

All Variants

SegregaJon of NA12878 heterozygous variants called as family, GQ>50, homozygous reference in other parent.


Pattern #2: Homozygous-alt variant

Trio Calling

NA12878

NA12892NA12891

NA12877

NA12889 NA12890

NA12879 NA12880 NA12881 NA12882 NA12883 NA12884 NA12885 NA12886 NA12887 NA12888 NA12893

0/1

1/10/0

0/1 0/1 0/10/10/10/1 0/1 0/1 0/1 0/1


Segregation of homo-alt variants

0

20,000

40,000

60,000

80,000

100,000

120,000

1 2 3 4 5 6 7 8 9 10 11

SNV coun

t


SNV

0

100

200

300

400

500

600

700

1 2 3 4 5 6 7 8 9 10 11

MNP coun

t


MNP

0

2,000

4,000

6,000

8,000

10,000

12,000

1 2 3 4 5 6 7 8 9 10 11

inde

l cou

nt


indel

0

20,000

40,000

60,000

80,000

100,000

120,000

1 2 3 4 5 6 7 8 9 10 11

Varia

nt cou

nt


All Variants

SegregaJon of NA12878 homozygous alternaJve variants called as family, GQ>50, homozygous reference in other parent.


False positive estimate by segregation GT Type All variants SNV MNP indel Het

TP (10-‐11) 123672 110262 693 12717

FP (1-‐8) 1901 1000 47 854

FP% 1.40% 0.88% 1.42% 5.67% Homo-‐alt

TP (2-‐10) 373260 329642 2258 41360

FP (1,11) 4457 3672 36 749

FP% 1.18% 1.10% 1.57% 1.78% Overall

TP 496932 439904 2951 54077

FP 6358 4672 83 1603 Overall FP% 1.26% 1.05% 2.74% 2.88%


Data imputation by pedigree caller

•  For genomes with no data use population priors –  With care can iterate over offspring then each of parents

independently –  Avoid exponential explosion so can do whole extended

family in one calling step


Imputation of family members with no data

Simulated data

True

PosiJves

False PosiJves

1 offspring

2 offspring

4 offspring

4 offspring + father


ROC vs NA12878 imputed baseline



de novo mutation identification

Call set de novo

candidates de novo germline*

de novo somaBc* TP/FP

Singleton calls 16,902 49 (100%) 941 (99%) 1:17

Trio calls 2,205 49 (100%) 941 (99%) 1:2.2

de novo MutaBon Accuracy (NA12878)

*SensiJvity vs. Conrad et al. (2011) validated dataset of germline and somaJc cell line de novo mutaJons.

–  Uses the parental genomes to identify & score de novo mutations in offspring

–  Greater than 7X improvement in precision to find de novo mutations vs. naïve methods

NA12878

NA12891 NA12892


Status

•  Working through the complete trio datasets for producing joint pedigree calls for NA12878 trio – Aiming for a trio call set and another that

includes full Platinum pedigree data – There is disproportionally more data for

NA12878 than her parents or offspring •  Comprehensive segregation analysis that

includes all Mendelian patterns •  Phasing analysis to identify variants that are

inconsistent with transmitted phases


Issues

•  How to integrate pedigree calls with other data? – Variants that segregate appropriately

candidates for inclusion in baseline – Variants that don’t segregate appropriately

candidates for removal of baseline –  Improvement of baseline genotypes using

pedigree-based genotypes •  Use of the imputed NA12878 baseline •  Creation of a more inclusive baseline for ROC

curves to compare new methods and select thresholds


Acknowledgements

•  RTG team at Hamilton, New Zealand –  Led by John Cleary, CTO

•  RTG team at San Bruno, CA –  Sahar Malakshah –  Minita Shah –  Brian Hilbush

•  Michael Eberle, Illumina, Inc. – Platinum Data •  Justin Zook, NIST •  1000 Genomes Project

© 2013 Real Time Genomics, Inc. All rights reserved. US Patent 7,640,256. Other patents pending. For research use only. Not for diagnosJc applicaJons.

Technology

Aug2013 real time genomics trio pedigree analysis