Notes from Meeting
Consider a single lineage for now.
= frequency of "1" allele at SNP j in the pool (i.e. the true frequency of the 1 allele in the pool)
= number of "0", "1" alleles at SNP j ()
~ Normal approximation to binomial
The variance of this distribution results from error due to binomial sampling.
To simplify, we just plug in for
frequency of reference allele in group i, replicate and SNP j.
vector of frequencies
Without loss of generality, we assume that the putative selected site is site
We assume a prior on our vector of frequencies based on our panel of SNPs of dimension
where if i = j or if i not equal to j
The conditional distribution is easily obtained when we use a result derived here.
And equivalently we could derive the distribution
- Likelihood for frequency a the test SNP t given all data
Confused here, can we just use the expression derived above for . Also, isn't ~
and ~ . But, how do we then incorporate into the likelihood calculation?
But maybe we want to incorporate dispersion and measurement error parameters
~ The parameter allows for over-dispersion
~ where allows for measurement error.
and I don't understand . Shouldn't it come from (2.12) and not (2.13) - ask Matthew