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Betaspikes
The Beta distribution approach
PAULA TATARU
AARHUS
UNIVERSITY
Bioinformatics
Research Centre
Aarhus, October 23rd 2014
Modelling allele frequency data under the
Wright Fisher model of drift, mutation and selection
Joint work with Thomas Bataillon and Asger Hobolth
Allele frequencies: the Beta distribution approach
Paula Tataru paula@birc.au.dk
AARHUS
UNIVERSITY
Bioinformatics
Research Centre
Motivation
›Inference population parameters from DNA data
› mutation rates
› selection coefficients
› split times
› variable population size back in time
›Backward in time (coalescent)
›Forward in time (Wright Fisher)
2
Allele frequencies: the Beta distribution approach
Paula Tataru paula@birc.au.dk
AARHUS
UNIVERSITY
Bioinformatics
Research Centre
3
The Wright Fisher model: Drift only
Allele frequencies: the Beta distribution approach
Paula Tataru paula@birc.au.dk
AARHUS
UNIVERSITY
Bioinformatics
Research Centre
4
The Wright Fisher model: Mutations
Allele frequencies: the Beta distribution approach
Paula Tataru paula@birc.au.dk
AARHUS
UNIVERSITY
Bioinformatics
Research Centre
5
The Wright Fisher model: Selection
Allele frequencies: the Beta distribution approach
Paula Tataru paula@birc.au.dk
AARHUS
UNIVERSITY
Bioinformatics
Research Centre
Allele frequency distribution: Drift only
6
Allele frequencies: the Beta distribution approach
Paula Tataru paula@birc.au.dk
AARHUS
UNIVERSITY
Bioinformatics
Research Centre
›Diffusion
› Kimura 1964
› Gautier & Vitalis 2013
› Malaspinas et al. 2012
› Steinrucken et al. 2013
› Zhao et al. 2013
›Moment based
› Normal distribution
› Nicholson et al. 2002
› Prickrell & Pritchard 2012
› Beta distribution
› Balding & Nichols 1995
› Siren et al. 2011
› Beta with spikes
7
Approximations to the Wright Fisher
Allele frequencies: the Beta distribution approach
Paula Tataru paula@birc.au.dk
AARHUS
UNIVERSITY
Bioinformatics
Research Centre
8
The Beta approximation: Main idea
›The density of Xt
›Use recursive approach to calculate
› mean and variance
Allele frequencies: the Beta distribution approach
Paula Tataru paula@birc.au.dk
AARHUS
UNIVERSITY
Bioinformatics
Research Centre
9
The Beta approximation: Drift only
Allele frequencies: the Beta distribution approach
Paula Tataru paula@birc.au.dk
AARHUS
UNIVERSITY
Bioinformatics
Research Centre
10
The Beta approximation: Drift only
Allele frequencies: the Beta distribution approach
Paula Tataru paula@birc.au.dk
AARHUS
UNIVERSITY
Bioinformatics
Research Centre
11
The Beta approximation: Drift only
Allele frequencies: the Beta distribution approach
Paula Tataru paula@birc.au.dk
AARHUS
UNIVERSITY
Bioinformatics
Research Centre
The Beta with spikes: Main idea
›The density of Xt
›Use recursive approach to calculate
› mean and variance
› loss and fixation probabilities
› mean and variance conditional on polymorphism
12
Allele frequencies: the Beta distribution approach
Paula Tataru paula@birc.au.dk
AARHUS
UNIVERSITY
Bioinformatics
Research Centre
Approximations: Drift only
13
Allele frequencies: the Beta distribution approach
Paula Tataru paula@birc.au.dk
AARHUS
UNIVERSITY
Bioinformatics
Research Centre
14
Approximations: Drift only
Allele frequencies: the Beta distribution approach
Paula Tataru paula@birc.au.dk
AARHUS
UNIVERSITY
Bioinformatics
Research Centre
15
The Beta with spikes: Drift only / Selection
Allele frequencies: the Beta distribution approach
Paula Tataru paula@birc.au.dk
AARHUS
UNIVERSITY
Bioinformatics
Research Centre
16
The Beta with spikes: Drift only / Selection
Allele frequencies: the Beta distribution approach
Paula Tataru paula@birc.au.dk
AARHUS
UNIVERSITY
Bioinformatics
Research Centre
17
The Beta with spikes: Drift only / Selection
Allele frequencies: the Beta distribution approach
Paula Tataru paula@birc.au.dk
AARHUS
UNIVERSITY
Bioinformatics
Research Centre
18
Inference of split times: Drift only
›Felsenstein’s peeling algorithm
›Numerically optimized likelihood
›5000 independent loci
›100 samples in each population
›40 data sets
Allele frequencies: the Beta distribution approach
Paula Tataru paula@birc.au.dk
AARHUS
UNIVERSITY
Bioinformatics
Research Centre
Inference of split times: Drift only
19
Allele frequencies: the Beta distribution approach
Paula Tataru paula@birc.au.dk
AARHUS
UNIVERSITY
Bioinformatics
Research Centre
Conclusions
›Beta with spikes: new approximation to the WF
› Quality of approximation
› Consistent
› Diffusion > Beta with spikes > Beta
› Simple mathematical formulation -> decrease in speed
› Inference of split times
› Beta with spikes ~ Kim Tree
20
Allele frequencies: the Beta distribution approach
Paula Tataru paula@birc.au.dk
AARHUS
UNIVERSITY
Bioinformatics
Research Centre
21
Loss and fixation probabilities

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PaulaTataruAarhus

  • 1. Betaspikes The Beta distribution approach PAULA TATARU AARHUS UNIVERSITY Bioinformatics Research Centre Aarhus, October 23rd 2014 Modelling allele frequency data under the Wright Fisher model of drift, mutation and selection Joint work with Thomas Bataillon and Asger Hobolth
  • 2. Allele frequencies: the Beta distribution approach Paula Tataru paula@birc.au.dk AARHUS UNIVERSITY Bioinformatics Research Centre Motivation ›Inference population parameters from DNA data › mutation rates › selection coefficients › split times › variable population size back in time ›Backward in time (coalescent) ›Forward in time (Wright Fisher) 2
  • 3. Allele frequencies: the Beta distribution approach Paula Tataru paula@birc.au.dk AARHUS UNIVERSITY Bioinformatics Research Centre 3 The Wright Fisher model: Drift only
  • 4. Allele frequencies: the Beta distribution approach Paula Tataru paula@birc.au.dk AARHUS UNIVERSITY Bioinformatics Research Centre 4 The Wright Fisher model: Mutations
  • 5. Allele frequencies: the Beta distribution approach Paula Tataru paula@birc.au.dk AARHUS UNIVERSITY Bioinformatics Research Centre 5 The Wright Fisher model: Selection
  • 6. Allele frequencies: the Beta distribution approach Paula Tataru paula@birc.au.dk AARHUS UNIVERSITY Bioinformatics Research Centre Allele frequency distribution: Drift only 6
  • 7. Allele frequencies: the Beta distribution approach Paula Tataru paula@birc.au.dk AARHUS UNIVERSITY Bioinformatics Research Centre ›Diffusion › Kimura 1964 › Gautier & Vitalis 2013 › Malaspinas et al. 2012 › Steinrucken et al. 2013 › Zhao et al. 2013 ›Moment based › Normal distribution › Nicholson et al. 2002 › Prickrell & Pritchard 2012 › Beta distribution › Balding & Nichols 1995 › Siren et al. 2011 › Beta with spikes 7 Approximations to the Wright Fisher
  • 8. Allele frequencies: the Beta distribution approach Paula Tataru paula@birc.au.dk AARHUS UNIVERSITY Bioinformatics Research Centre 8 The Beta approximation: Main idea ›The density of Xt ›Use recursive approach to calculate › mean and variance
  • 9. Allele frequencies: the Beta distribution approach Paula Tataru paula@birc.au.dk AARHUS UNIVERSITY Bioinformatics Research Centre 9 The Beta approximation: Drift only
  • 10. Allele frequencies: the Beta distribution approach Paula Tataru paula@birc.au.dk AARHUS UNIVERSITY Bioinformatics Research Centre 10 The Beta approximation: Drift only
  • 11. Allele frequencies: the Beta distribution approach Paula Tataru paula@birc.au.dk AARHUS UNIVERSITY Bioinformatics Research Centre 11 The Beta approximation: Drift only
  • 12. Allele frequencies: the Beta distribution approach Paula Tataru paula@birc.au.dk AARHUS UNIVERSITY Bioinformatics Research Centre The Beta with spikes: Main idea ›The density of Xt ›Use recursive approach to calculate › mean and variance › loss and fixation probabilities › mean and variance conditional on polymorphism 12
  • 13. Allele frequencies: the Beta distribution approach Paula Tataru paula@birc.au.dk AARHUS UNIVERSITY Bioinformatics Research Centre Approximations: Drift only 13
  • 14. Allele frequencies: the Beta distribution approach Paula Tataru paula@birc.au.dk AARHUS UNIVERSITY Bioinformatics Research Centre 14 Approximations: Drift only
  • 15. Allele frequencies: the Beta distribution approach Paula Tataru paula@birc.au.dk AARHUS UNIVERSITY Bioinformatics Research Centre 15 The Beta with spikes: Drift only / Selection
  • 16. Allele frequencies: the Beta distribution approach Paula Tataru paula@birc.au.dk AARHUS UNIVERSITY Bioinformatics Research Centre 16 The Beta with spikes: Drift only / Selection
  • 17. Allele frequencies: the Beta distribution approach Paula Tataru paula@birc.au.dk AARHUS UNIVERSITY Bioinformatics Research Centre 17 The Beta with spikes: Drift only / Selection
  • 18. Allele frequencies: the Beta distribution approach Paula Tataru paula@birc.au.dk AARHUS UNIVERSITY Bioinformatics Research Centre 18 Inference of split times: Drift only ›Felsenstein’s peeling algorithm ›Numerically optimized likelihood ›5000 independent loci ›100 samples in each population ›40 data sets
  • 19. Allele frequencies: the Beta distribution approach Paula Tataru paula@birc.au.dk AARHUS UNIVERSITY Bioinformatics Research Centre Inference of split times: Drift only 19
  • 20. Allele frequencies: the Beta distribution approach Paula Tataru paula@birc.au.dk AARHUS UNIVERSITY Bioinformatics Research Centre Conclusions ›Beta with spikes: new approximation to the WF › Quality of approximation › Consistent › Diffusion > Beta with spikes > Beta › Simple mathematical formulation -> decrease in speed › Inference of split times › Beta with spikes ~ Kim Tree 20
  • 21. Allele frequencies: the Beta distribution approach Paula Tataru paula@birc.au.dk AARHUS UNIVERSITY Bioinformatics Research Centre 21 Loss and fixation probabilities