RT Journal
A1 Bhaskar, Anand
A1 Wang, Y.X. Rachel
A1 Song, Yun S.
T1 Efficient inference of population size histories and locus-specific mutation rates from large-sample genomic variation data
JF Genome Research 
JO Genome Research 
YR 2015 
FD February 01 
VO 25 
IS 2 
SP 268 
OP 279 
DO 10.1101/gr.178756.114 
UL http://genome.cshlp.org/content/25/2/268.abstract 
AB With the recent increase in study sample sizes in human genetics, there has been growing interest in inferring historical population demography from genomic variation data. Here, we present an efficient inference method that can scale up to very large samples, with tens or hundreds of thousands of individuals. Specifically, by utilizing analytic results on the expected frequency spectrum under the coalescent and by leveraging the technique of automatic differentiation, which allows us to compute gradients exactly, we develop a very efficient algorithm to infer piecewise-exponential models of the historical effective population size from the distribution of sample allele frequencies. Our method is orders of magnitude faster than previous demographic inference methods based on the frequency spectrum. In addition to inferring demography, our method can also accurately estimate locus-specific mutation rates. We perform extensive validation of our method on simulated data and show that it can accurately infer multiple recent epochs of rapid exponential growth, a signal that is difficult to pick up with small sample sizes. Lastly, we use our method to analyze data from recent sequencing studies, including a large-sample exome-sequencing data set of tens of thousands of individuals assayed at a few hundred genic regions.