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Diffusion Approximation for Demographic Inference∂a∂i implements a method for demographic inference from genetic data, based on a diffusion approximation to the allele frequency spectrum. One of ∂a∂i's main benefits is speed: fitting a two-population model typically takes around 10 minutes, and run time is independent of the number of SNPs in your data set. ∂a∂i is also flexible, handling up to three simultaneous populations, with arbitrary timecourses for population size and migration, plus the possibility of admixture and population-specific selection. The code is young but has already been used in several publications. Originally ∂a∂i was initially developed by Ryan Gutenkunst in the labs of Scott Williamson and Carlos Bustamante in Cornell's Department of Biological Statistics and Computational Biology. Ryan is now faculty in Molecular and Cellular Biology at the University of Arizona, and his group continues to work on ∂a∂i. News
This release fixes a long-standing bug in make_fux_table. (Testing suggests that in almost all cases the bug had little effect on results.) Also fixed is a bug that prevented optimizations from succeeding.
This release improves support for modeling admixture. It turns out that when the admixture methods in PhiManip are used, this can result in oscillations in the calculated frequency spectrum as the grid size is changes, which invalidates extrapolation. One solution is to run with pts_l of length one, so there is no extrapolation. Another solution, if the admixture is the last event in your model, is to implement admixture using the new admix_props argument to Spectrum.from_phi, rather than using the PhiManip methods.
This release introduces support for modeling temporal samples, in which samples from different timepoints are compared. This is implemented through freeze arguments to the Integration functions. See the manual under "Ancient Sequences" for more information.
This release includes numerous small bug fixes and enhancements. Also, binaries are now provided for Python 2.7. Example
The above plot summarizes the result of fitting a model the joint frequency spectrum of genetic variation between the Yoruba (YRI) and CEPH European (CEU) populations. The data is derived from the Environmental Genome Project SNPs database. The upper left panel is the data, and the upper right is the result of a demographic model whose parameters have been optimized using ∂a∂i. The lower left panel is the residuals between model and data (red means the model predicts too many SNPs in that bin) and the lower right is a histogram of the residuals. The model involves population growth in the ancestral population, followed by divergence of the CEU population with a bottleneck and exponential growth. It contains 7 free parameters and took a few minutes to fit using ∂a∂i. |
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