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* adding DFE for Arabidopsis * updated __init__.py, and HomSap dfe file
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Original file line number | Diff line number | Diff line change |
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import stdpopsim | ||
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_species = stdpopsim.get_species("AraTha") | ||
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########################################################### | ||
# | ||
# DFEs | ||
# | ||
########################################################### | ||
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def _HuberDFE(): | ||
id = "Gamma_H18" | ||
description = "Deleterious Gamma DFE" | ||
long_description = """ | ||
Return negative (no neutral, in this case) MutationType()s | ||
representing an Arabidopsis DFE. From Huber et al. (2018). | ||
Gamma parameters are based on Supplementary Table 4, | ||
the genome-wide, additive-only model for A. LYRATA- due to | ||
challenges with simulating with selfing for A. thaliana. | ||
The Supplementary Table 4 DFEs are not noted to contain | ||
any neutral mutations (in contrast, Supplementary Table 3 | ||
notes neutral proportions for two other DFEs), and in the | ||
main text including neutral mutations seems like a | ||
supplementary analysis rather than the main strategy. | ||
""" | ||
citations = [ | ||
stdpopsim.Citation( | ||
author="Huber et al.", | ||
year=2018, | ||
doi="https://doi.org/10.1038/s41467-018-05281-7", | ||
reasons=stdpopsim.CiteReason.DFE, | ||
) | ||
] | ||
neutral = stdpopsim.MutationType() | ||
gamma_shape = 0.27 # shape | ||
gamma_mean = -0.0004 # expected value | ||
h = 0.5 # dominance coefficient | ||
negative = stdpopsim.MutationType( | ||
dominance_coeff=h, | ||
distribution_type="g", # gamma distribution | ||
distribution_args=[gamma_mean, gamma_shape], | ||
) | ||
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return stdpopsim.DFE( | ||
id=id, | ||
description=description, | ||
long_description=long_description, | ||
mutation_types=[neutral, negative], | ||
proportions=[ | ||
0, | ||
1.0, | ||
], | ||
citations=citations, | ||
) | ||
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_species.add_dfe(_HuberDFE()) |
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