9,133 research outputs found
Distortion of genealogical properties when the sample is very large
Study sample sizes in human genetics are growing rapidly, and in due course
it will become routine to analyze samples with hundreds of thousands if not
millions of individuals. In addition to posing computational challenges, such
large sample sizes call for carefully re-examining the theoretical foundation
underlying commonly-used analytical tools. Here, we study the accuracy of the
coalescent, a central model for studying the ancestry of a sample of
individuals. The coalescent arises as a limit of a large class of random mating
models and it is an accurate approximation to the original model provided that
the population size is sufficiently larger than the sample size. We develop a
method for performing exact computation in the discrete-time Wright-Fisher
(DTWF) model and compare several key genealogical quantities of interest with
the coalescent predictions. For realistic demographic scenarios, we find that
there are a significant number of multiple- and simultaneous-merger events
under the DTWF model, which are absent in the coalescent by construction.
Furthermore, for large sample sizes, there are noticeable differences in the
expected number of rare variants between the coalescent and the DTWF model. To
balance the tradeoff between accuracy and computational efficiency, we propose
a hybrid algorithm that utilizes the DTWF model for the recent past and the
coalescent for the more distant past. Our results demonstrate that the hybrid
method with only a handful of generations of the DTWF model leads to a
frequency spectrum that is quite close to the prediction of the full DTWF
model.Comment: 27 pages, 2 tables, 14 figure
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Research Notes: Genotype response to soybean cyst nematodes in different soil sources
Soybean cyst nematode was first observed in North Carolina as a pest on soybeans in 1954. Within a few years, it was reported from Virginia, Tennessee, Arkansas, Missouri and Illinois. This necessitated the screening of the soybean germplasm, which lead to the discovery of the following lines carrying resistance to SCN
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