Models and their benefits. Models + Data 1. probability of data (statistics...) 2. probability of individual histories 3. hypothesis testing 4. parameter estimation
Haploid Model Diploid Model Wright-Fisher Model of Population Reproduction i. Individuals are made by sampling with replacement in the previous generation. ii. The probability that 2 alleles have same ancestor in previous generation is 1/2N Individuals are made by sampling a chromosome from the female and one from the male previous generation with replacement Assumptions 1.Constant population size 2.No geography 3.No Selection 4.No recombination
10 Alleles’ Ancestry for 15 generations
Mean, E(X 2 ) = 2N. Ex.: 2N = , Generation time 30 years, E(X 2 ) = years. Waiting for most recent common ancestor - MRCA P(X 2 = j) = (1-(1/2N)) j-1 (1/2N) Distribution until 2 alleles had a common ancestor, X 2 ?: P(X 2 > j) = (1-(1/2N)) j P(X 2 > 1) = (2N-1)/2N = 1-(1/2N) 1 2N j j
P(k):=P{k alleles had k distinct parents} 1 2N 1 2N *(2N-1) *..* (2N-(k-1)) =: (2N) [k] (2N) k k -> any k -> k k -> k-1 Ancestor choices: k -> j For k << 2N: S k,j - the number of ways to group k labelled objects into j groups.(Stirling Numbers of second kind.
Expected Height and Total Branch Length Expected Total height of tree: H k = 2(1-1/k) i.Infinitely many alleles finds 1 allele in finite time. ii. In takes less than twice as long for k alleles to find 1 ancestors as it does for 2 alleles. Expected Total branch length in tree, L k : 2*(1 + 1/2 + 1/ /(k-1)) ca= 2*ln(k-1) k 1/ /(k-1) Time Epoch Branch Lengths
6 Realisations with 25 leaves Observations: Variation great close to root. Trees are unbalanced.
Sampling more sequences The probability that the ancestor of the sample of size n is in a sub-sample of size k is Letting n go to infinity gives (k-1)/(k+1), i.e. even for quite small samples it is quite large.
Final Aligned Data Set: Infinite Site Model
Recombination-Coalescence Illustration Copied from Hudson 1991 Intensities Coales. Recomb. 1 2 3 2 6 2 3 (2+b) 1 (1+b) 0 b