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Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological)...

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Variant Simulation Tools Bo Peng Sep 25, 2014
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Page 1: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Variant Simulation Tools

Bo Peng Sep 25, 2014

Page 2: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Genetic Simulations

Page 3: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Why perform simulations?

• Validate  sta+s+cal  methods  using  simulated  data  based  on  specific  assump+ons  

To  get  data  that  match  these  (unrealis+c)  assump+ons  of  our  

methods    

• Simulate  data  using  specific  models  and  compare  them  to  empirical  data  

• Infer  parameters  from  best-­‐match  simula+ons  

To  evaluate  condi+ons  that  could  have  given  rise  to  current  

observa+ons  

• Calculate  empirical  sta+s+cal  power  by  applying  sta+s+cal  methods  to  a  large  number  of  simulated  data  

• Compare  power  of  mul+ple  methods  

To  get  mul+ple  replicates  of  data  

• Genotypes  of  large  pedigree,  ancestral  popula+ons  • Samples  of  very  rare  disease  

To  obtain  informa+on  that  are  unavailable  or  too  expensive  to  

obtained  empirically  

• What  are  the  impact  of  demographic  and  gene+c  features  of  a  popula+on?  

• Evaluate  how  changes  to  a  system  could  change  its  aHributes  (cancer  interven+on)  

To  look  backward  and  forward  in  +me  

Page 4: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

What to simulate?

•  Haploid and Diploid sequences •  Genetic markers •  Sex chromosomes •  Mitochondrial DNA •  RNA sequence •  Protein sequence

•  SNP  markers  •  Microsatellite  markers  •  Inser+ons,  dele+ons,  inversion  •  Large  indels,  structural  varia+on  •  Copy  number  varia+on  •  Genotyping  error  •  Missing  data  

•  Qualita+ve  and  quan+ta+ve  traits  •  Random  sample  •  Extreme  traits  •  Case  control  data  •  Pedigree  data  •  Output  from  genotyping  and  other  

plaRorms  

•  Impact  of  boHleneck  •  Impact  of  migra+on  •  Impact  of  natural  selec+on  •  Impact  of  popula+on  expansion  •  Impact  of  recombina+on  

Page 5: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Theoretical simulations

Pros:  •  Efficient  •  Matching  specific  assump+ons  

exactly  

Cons:  •  Difficult  to  handle  mul+ple  

assump+ons  •  Difficult  to  simulate  long  genomic  

regions  with  linked  loci  

Ideal  for:  •  Simple  data  matching  specific  

assump+ons  

Distribution of features

60% 15% 25%

Page 6: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Resampling-based simulations

Empirical Samples

Pros:  •  Efficient  •  Realis+c  samples  •  Able  to  simulate  genome-­‐wide  

samples  

Cons:  •  Difficult  to  match  specified  condi+ons  •  Source  data  dependent  •  Confounding  genomic  features  •  Difficult  to  introduce  addi+onal  

gene+c  varia+ons  

Idea  for:  •  Long  genomic  regions  with  realis+c  

features  

Page 7: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Coalescent-based Simulation

Most recent common ancestor

Tim

e / G

ener

atio

n

Pros:  •  Very  efficient  •  Support  many  muta+on  and  

migra+on  models  

Cons:  •  Difficult  to  simulate  genotype-­‐

dependent  or  diploid-­‐specific  features  e.g.  natural  selec+on  and  penetrance  models  

•  Difficult  to  simulate  long  range  genomic  regions  with  recombina+on  

•  Does  not  provide  good  plaRorm  for  complex  disease  

Ideal  for:  •  Large  number  of  short  neutral  

sequences  

Page 8: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Forward-time Simulation

Tim

e / G

ener

atio

n

Pros:  •  Extremely  powerful  and  flexible  in  

modeling  natural  selec+on,  penetrance,  and  study  designs  

•  Complete  informa+on  about  ancestral  popula+ons  

Cons:  •  Can  be  hard  to  make  realis+c  •  Difficult  to  simulate  long  genomic  

regions  and  rare  phenotype  

Ideal  for:  •  Observa+onal  simula+ons  •  Samples  under  complex  evolu+onary  

scenarios  and  study  designs  

Page 9: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Gene Dropping

Pros:  •  Efficient  •  Adapt  to  arbitrary  pedigree  structure  

Cons:  •  Difficult  to  simulate  genotype  

condi+oning  on  specified  traits  

Ideal  for:  •  Simula+ng  pedigree  data  from  

exis+ng  pedigree  structures  

Page 10: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Simulation of Genotypes and Phenotypes association – GAW16

Page 11: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Sample Applications

Page 12: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Simulation of GWA Studies

Peng  &  Amos,  BMC  Bioinforma+cs,  2010    

Page 13: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Impact of population structure

Page 14: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Rare variant association analysis Fixed effect w/ 100% RV deleterious. Prevalence 1%. N = 300:300

Odds ratio per causal rare variant

Powe

r

0%

10%

20%

30%

40%

50%

●●

●●

OR=1 OR=1.5 OR=2 OR=3

Method●● calpha●● CMC

CMCSTKBAC

●● KBACSTMZRareCoverRBTRVESKATVTVTfisherWSSWSSPM

Page 15: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Design and implementation

Page 16: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Why yet another simulator?

Many new methods are using prior biological knowledge in some way, for filtering, for pathway analysis, and for Bayesian priors

Most of our models follow standard genetic models (dominant, recessive, additive etc) and simple phenotype models.

THE  Truth  Truth  that  we  think  we  know  

Truth  that  we  can  model  

Truth  that  we  can  simulate  

GAP  to  be  filled  

Page 17: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Variant Simulation Tools

Peng,  Gene+c  Epi,  2014  

VST  is  a  simula+on    tools  for  post-­‐GWA  gene+c  epidemiological  studies,  with  emphases  on  realism,  user-­‐friendliness  and  reproducibility.    

Page 18: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Variant Tools Repository

Two-­‐%er  design  Tested  models  

Simulated  datasets  

Page 19: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Simulation Specification Files

Variant  tools  pipeline    Mul+ple  models  in  one  spec  file    Can  execute  arbitrary  commands    Allow  addi+onal  pipeline  steps  and  func+ons  in  Python    NOT  user-­‐friendly  

Page 20: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Variant Tools + simuPOP

•  Mutant-based storage model for the simulation of rare variants

•  Fine-scale recombination with hotspot

•  Flexible natural selection models

•  Demographic models

•  Storage, annotation, and manipulation of variants

•  Pipeline mechanism •  User interface •  Gene annotation •  Variant tools

repository •  Integration with

Variant Association Tools

Page 21: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Simple command line interface

•  Commands to show all simulation models vtools  show  simulations  

•  Clear documentation vtools  show  simulation  SPECFILE  

•  Simple interface with no or few parameters vtools  simulate  SPECFILE  [model]  [opt]

•  Downloadable simulated datasets vtools  show  snapshots

Page 22: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Realistic Demographic Models

Out  of  Africa  Model  

SeHlement  of  New  World  Model  

Cosi  model  

Schaffner  et  al,  genome  research,  2005  Gutenkunst,  PLoS  Gene+cs,  2009  

Page 23: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Nucleotide mutation models

•  Jukes  Cantor  1969  model  •  Kimura  1980  model  •  Felsenstein  1981  model  •  HKY  1985  model  •  …  

•  Muta+ng  real  nucleo+de  sequences  of  specified  regions  of  the  human  genome  

•  Allow  mul+ple-­‐alterna+ve  alleles  

•  Can  model  difference  in  transi+on  and  transversion  rates  

Page 24: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Fine-scale recombination map

Page 25: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Protein-based selection and trait models •  Muta+ons  in  introns  are  

silent  

•  One  muta+on  can  cause  different  fitness  effects  for  mul+ple  isoforms  of  a  gene  

•  One  muta+on  can  have  different  fitness  effect  due  to  the  occurrence  of  another  muta+on  

•  Different  muta+ons  can  happen  at  the  same  loca+on  

•  Fitness  effect  for  regular  non-­‐synonymous,  stop-­‐gain  and  stop-­‐loss  muta+ons.  

Page 26: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Example 1

Page 27: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Model Details

•  chr17:41,200,001-41,263,000 (63,000 bp) •  NM_007294, NM_007297, NM_007298,

NM_007299, NM_007300 (BRCA1) •  5337 (8.47%) in coding regions of one of the

isoforms •  Demographic model of European populations

(Kryukov et al, 2007) •  Mutation rate 1.8x10-8 using a Jukes-Cantor

model •  Constant fitness values 0.005, 0.02, and 0.1

for missense, stoploss, and stopgain mutations

Page 28: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Number of alleles in sample

Num

ber o

f SN

Ps

010

020

030

040

0

1 2 3 4 5 6 7 8 9 10−69 70+

ms (neutral)VST neutralVST selectionVST resampling1000 genomes

a

Number of alleles in sample

Num

ber o

f SN

Ps in

cod

ing

regi

ons

010

2030

40

1 2 3 4 5 6 7 8 9 10−69 70+

b

Page 29: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Example 2

Page 30: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

G Protein Coupled Receptors signaling pathway

•  20 genes in the GPCR pathway on chromosomes 6, 8, and 10 and X

•  Overlap with 27 isoforms of 15 genes

•  Coding regions of these genes range from 563 to 1818 base pairs and represents 16.2% of the total simulated region (17,841 of 110,387 bp)

•  Five causal genes

Page 31: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Model details

•  Settlement of New World model with AF, AS, EU, MX, and MXL populations.

•  K80 mutation model with an ti/tv ratio of 2 •  Recombination rates from 6.14 × 10–9 to 6.23 × 10–6

•  Fitness effect of 0.0001, 0.0001, and 0.001 for missense, stoploss, and stopgain mutations

•  Draw case controls samples from EU, MXL or EU/AS (mismatch) populations

•  Analyze all variants or non-synnonymous mutations (annotated by snpEff)

Page 32: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

All variants

−log10(p−value) for analyses with all variants

CCNB1> CCNB2

CCNB3CCND2

> CCNE1CCNE2

> CCNG1> CCNG2

CDK1PPM1D

0 20 40 60 80

5.2%5.2%

5.4%

5.5%

5.5%

5.1%48.1%

48.9%

43.2%45.2%

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0 20 40 60 80

34.2%34.9%

34.4%

34.4%

34.2%

34.0%48.8%

48.8%

46.3%47.5%

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Mismatch1000

CCNB1> CCNB2

CCNB3CCND2

> CCNE1CCNE2

> CCNG1> CCNG2

CDK1PPM1D 5.9%

5.9%

5.7%

5.6%

5.9%

6.0%58.2%

59.6%

52.1%55.2%

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6.4%5.7%

6.2%

6.2%

6.1%

6.6%76.6%

76.7%

70.8%73.1%

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●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

MexicanAmerican2000

38.5%39.4%

38.0%

39.5%

38.6%

38.9%52.9%

53.2%

51.5%51.5%

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Mismatch2000

Page 33: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Limit to non-synonymous variants

−log10(p−value) for analyses with non−synonymous variants

CCNB1> CCNB2

CCNB3CCND2

> CCNE1CCNE2

> CCNG1> CCNG2

CDK1PPM1D

0 20 40 60

5.8%5.3%

5.6%

5.5%

5.5%

5.3%54.7%

55.3%

50.2%52.0%

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●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●● ●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●

MexicanAmerican1000

0 20 40 60

33.9%34.8%

35.1%

34.8%

34.7%

36.3%50.5%

51.7%

48.5%50.0%

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Mismatch1000

CCNB1> CCNB2

CCNB3CCND2

> CCNE1CCNE2

> CCNG1> CCNG2

CDK1PPM1D 5.8%

6.1%

5.7%

5.7%

5.6%

5.2%65.1%

65.9%

59.3%62.4%

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European2000

0 20 40 60

6.4%5.3%

5.9%

5.8%

6.0%

5.6%81.4%

81.2%

76.0%78.0%

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MexicanAmerican2000

38.2%39.3%

39.4%

39.8%

39.2%

40.9%55.2%

56.2%

53.9%54.1%

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Mismatch2000

Page 34: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Discussions

Page 35: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Simple and powerful?

Variant  Tools  Repository  

VST  

VST  

model   datasets  

Simple  for    causal  users  

Some  work  for    normal  users   Complex  and  powerful  

for  advanced  users  

Page 36: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Reproducibility

•  Variant Tools repository encourages the sharing of simulation models

•  Option --seed to reproduce simulations •  Less option means easier reproducibility •  Available simulated datasets

Page 37: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Limitations

•  Limited to models that are provided by authors and power users (but the existing models are already comparable to other single-application tools)

•  Performance of the forward-time simulation engine – Scaling approach – Hybrid simulations

Page 38: Variant Simulation Tools · VST)is)a simulaon))tools) for)postGWA) genec epidemiological) studies,)with) emphases)on) realism, user= friendliness)and) reproducibility.) Variant Tools

Acknowledgements

•  Grant 1R01HG005859  (Dr.  Paul  Scheet) •  The Prevent Cancer Foundation •  The Michael and Susan Dell Foundation •  The Chapman Foundation •  MD Anderson High Performance

Computing Cluster

•  Dr.  Paul  Scheet  •  Gao  Wang  •  Dr.  Biao  Li  •  Dr.  Xiaoming  Liu  •  Dr.  John  Weinstein  


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