Module `simuPOP.demography`¶

This module provides some commonly used demographic models. In addition to several migration rate generation functions, it provides models that encapsulate complete demographic features of one or more populations ( population growth, split, bottleneck, admixture, migration). These models provides:

The model itself can be passed to parameter subPopSize of a mating scheme to determine the size of the next generation. More importantly, it performs necessary actions of population size change when needed.
The model provides attribute num_gens, which can be passed to parameter gens of Simulator.evolve or Population.evolve function. A demographic model can also terminate an evolutionary process by returnning an empty list so gens=model.num_gens is no longer required.

Function migrIslandRates¶

simuPOP.demography.migrIslandRates(r, n)¶

migration rate matrix

     x m/(n-1) m/(n-1) ....
     m/(n-1) x ............
     .....
     .... m/(n-1) m/(n-1) x

where x = 1-m

Function migrHierarchicalIslandRates¶

simuPOP.demography.migrHierarchicalIslandRates(r1, r2, n)¶

Return the migration rate matrix for a hierarchical island model where there are different migration rate within and across groups of islands.

r1: Within group migration rates. It can be a number or a list of numbers for each group of the islands.
r2: Across group migration rates which is the probability that someone will migrate to a subpopulation outside of his group. A list of r2 could be specified for each group of the islands.
n: Number of islands in each group. E.g. n=[5, 4] specifies two groups of islands with 5 and 4 islands each.

For individuals in an island, the probability that it remains in the same island is 1-r1-r2 (r1, r2 might vary by island groups), that it migrates to another island in the same group is r1 and migrates to another island outside of the group is r2. migrate rate to a specific island depends on the size of group.

Function migrSteppingStoneRates¶

simuPOP.demography.migrSteppingStoneRates(r, n, circular=False)¶

migration rate matrix for circular stepping stone model (X=1-m)

X   m/2               m/2
m/2 X   m/2           0
0   m/2 x   m/2 ......0
...
m/2 0 ....       m/2  X

or non-circular

       X   m/2               m/2
       m/2 X   m/2           0
       0   m/2 X   m/2 ......0
       ...
       ...              m   X

This function returns [[1]] when there is only one subpopulation.

Function migrtwoDSteppingStoneRates¶

simuPOP.demography.migr2DSteppingStoneRates(r, m, n, diagonal=False, circular=False)¶: migration rate matrix for 2D stepping stone model, with or without diagonal neighbors (4 or 8 neighbors for central patches). The boundaries are connected if circular is True. Otherwise individuals from corner and bounary patches will migrate to their neighbors with higher probability.

class EventBasedModel¶

class simuPOP.demography.EventBasedModel¶

An event based demographic model in which the demographic changes are triggered by demographic events such as population growth, split, join, and admixture. The population size will be kept constant if no event is applied at a certain generation.

EventBasedModel(events=[], T=None, N0=[], ops=[], infoFields=[])¶: A demographic model that is driven by a list of demographic events. The events should be subclasses of DemographicEvent, which have similar interface as regular operators with the exception that applicable parameters begin, end, step, at are relative to the demographic model, not the population.

plot(filename='', title='', initSize=[])¶: Evolve a haploid population using a RandomSelection mating scheme using the demographic model. Print population size changes duringe evolution. An initial population size could be specified using parameter initSize for a demographic model with dynamic initial population size. If a filename is specified and if matplotlib is available, this function draws a figure to depict the demographic model and save it to filename. An optional title could be specified to the figure. Note that this function can not be plot demographic models that works for particular mating schemes (e.g. genotype dependent).

class DemographicEvent¶

class simuPOP.demography.DemographicEvent¶

A demographic events that will be applied to one or more populations at specified generations. The interface of a DemographicEvent is very similar to an simuPOP operator, but the applicable parameters are handled so that the generations are relative to the demographic model, not the populations to which the event is applied.

DemographicEvent(ops=[], output='', begin=0, end=-1, step=1, at=[], reps=True, subPops=ALL_AVAIL, infoFields=[])¶: Create a demographic event that will be applied at specified generations according to applicability parameters reps, begin, end, step and at. Parameter subPops is usually used to specify the subpopulations affected by the event. One or more simuPOP operators, if specified in ops, will be applied when the event happens. Parameters output and infoFields are currently ignored.

apply(pop)¶

class ExpansionEvent¶

class simuPOP.demography.ExpansionEvent¶

A demographic event that increase applicable population size by N*r (to size N*(1+r)), or s (to size N+s) at each applicable generation. The first model leads to an exponential population expansion model with rate r (N(t)=N(0)*exp(r*t)), where the second model leads to an linear population growth model (N(t)=N(0)+s*t) and this is why the parameter is called slopes. Note that if both population size and r are small (e.g. N*r<1), the population might not expand as expected.

ExpansionEvent(rates=[], slopes=[], capacity=[], name='', ops=[], output='', begin=0, end=-1, step=1, at=[], reps=True, subPops=ALL_AVAIL, infoFields=[])¶: A demographic event that expands all or specified subpopulations (subPops) exponentially by a rate of rates, or linearly by a slope of slopes, unless carray capacity (capacity) of the population has been reached. Parameter rates can be a single number or a list of rates for all subpopulations. Parameter slopes should be a number, or a list of numbers for all subpopulations. subPops can be a ALL_AVAIL or a list of subpopulation index or names. capacity can be empty (no limit on carrying capacity), or one or more numbers for each of the subpopulations.

apply(pop)¶

class ResizeEvent¶

class simuPOP.demography.ResizeEvent¶

A demographic event that resize specified subpopulations

ResizeEvent(sizes=[], names=[], removeEmptySubPops=False, ops=[], output='', begin=0, end=-1, step=1, at=[], reps=True, subPops=ALL_AVAIL, infoFields=[])¶: A demographic event that resizes given subpopulations subPops to new sizes (integer type), or sizes proportional to original sizes (if a float number is given). For example, sizes=[0.5, 500] will resize the first subpopulation to half of its original size, and the second subpopulation to size 500. If the new size is larger, existing individuals will be copied to sequentially, and repeatedly if needed. If the size of a subpopulation is 0 and removeEmptySubPops is True, empty subpopulations will be removed. A new set of names could be assigned to the population being resized.

apply(pop)¶

class SplitEvent¶

class simuPOP.demography.SplitEvent¶

A demographic event that splits a specified population into two or more subpopulations.

SplitEvent(sizes=[], names=[], ops=[], output='', begin=0, end=-1, step=1, at=[], reps=True, subPops=ALL_AVAIL, infoFields=[])¶: A demographic event that splits a subpopulation specified by subPops to two or more subpopulations, with specified sizes and names. sizes can be a list of numbers, proportions (e.g. [1., 500] keeps the original population and copies 500 individuals to create a new subpupulation). Note that sizes and names, if specified, should include the source subpopulation as its first element.

apply(pop)¶

class MergeEvent¶

class simuPOP.demography.MergeEvent¶

A demographic event that merges one or more subpopulation to a single one.

MergeEvent(name='', ops=[], output='', begin=0, end=-1, step=1, at=[], reps=True, subPops=ALL_AVAIL, infoFields=[])¶: A demographic event that merges subpopulations into a single subpopulation. The merged subpopulation will have the name of the first merged subpopulation unless a separate name is supported.

apply(pop)¶

class AdmixtureEvent¶

class simuPOP.demography.AdmixtureEvent¶

This event implements a population admixture event that mix individuals from specified subpopulations to either a new subpopulation or an existing subpopulation.

AdmixtureEvent(sizes=[], toSubPop=None, name='', ops=[], output='', begin=0, end=-1, step=1, at=[], reps=True, subPops=ALL_AVAIL, infoFields=[])¶: Create an admixed population by choosing individuals from all or specified subpopulations (subPops) and creating an admixed population toSubPop. The admixed population will be appended to the population as a new subpopulation with name name if toSubPop is None (default), or replace an existing subpopulation with name or index toSubPop. The admixed population consists of individuals from subPops according to specified sizes. Its size is maximized to have the largest number of individuals from the source population when a new population is created, or equal to the size of the existing destination population. The parameter sizes should be a list of float numbers between 0 and 1, and add up to 1 (e.g. [0.4, 0.4, 0.2], although this function ignores the last element and set it to 1 minus the sum of the other numbers). Alternatively, parameter sizes can be a list of numbers used to explicitly specify the size of admixed population and number of individuals from each source subpopulation. In all cases, the size of source populations will be kept constant.

apply(pop)¶

class InstantChangeModel¶

class simuPOP.demography.InstantChangeModel¶

A model for instant population change (growth, resize, merge, split).

InstantChangeModel(T=None, N0=[], G=[], NG=[], ops=[], infoFields=[], removeEmptySubPops=False)¶: An instant population growth model that evolves a population from size N0 to NT for T generations with population size changes at generation G to NT. If G is a list, multiple population size changes are allowed. In that case, a list (or a nested list) of population size should be provided to parameter NT. Both N0 and NT supports fixed (an integer), dynamic (keep passed poulation size) and proportional (an float number) population size. Optionally, one or more operators (e.g. a migrator) ops can be applied to population. Required information fields by these operators should be passed to parameter infoFields. If removeEmpty option is set to True, empty subpopulation will be removed. This option can be used to remove subpopulations.

plot(filename='', title='', initSize=[])¶: Evolve a haploid population using a RandomSelection mating scheme using the demographic model. Print population size changes duringe evolution. An initial population size could be specified using parameter initSize for a demographic model with dynamic initial population size. If a filename is specified and if matplotlib is available, this function draws a figure to depict the demographic model and save it to filename. An optional title could be specified to the figure. Note that this function can not be plot demographic models that works for particular mating schemes (e.g. genotype dependent).

class ExponentialGrowthModel¶

class simuPOP.demography.ExponentialGrowthModel¶

A model for exponential population growth with carry capacity

ExponentialGrowthModel(T=None, N0=[], NT=None, r=None, ops=[], infoFields=[])¶: An exponential population growth model that evolves a population from size N0 to NT for T generations with r*N(t) individuals added at each generation. N0, NT and r can be a list of population sizes or growth rates for multiple subpopulations. The initial population will be resized to N0 (split if necessary). Zero or negative growth rates are allowed. The model will automatically determine T, r or NT if one of them is unspecified. If all of them are specified, NT is intepretted as carrying capacity of the model, namely the population will keep contant after it reaches size NT. Optionally, one or more operators (e.g. a migrator) ops can be applied to population.

plot(filename='', title='', initSize=[])¶: Evolve a haploid population using a RandomSelection mating scheme using the demographic model. Print population size changes duringe evolution. An initial population size could be specified using parameter initSize for a demographic model with dynamic initial population size. If a filename is specified and if matplotlib is available, this function draws a figure to depict the demographic model and save it to filename. An optional title could be specified to the figure. Note that this function can not be plot demographic models that works for particular mating schemes (e.g. genotype dependent).

class LinearGrowthModel¶

class simuPOP.demography.LinearGrowthModel¶

A model for linear population growth with carry capacity.

LinearGrowthModel(T=None, N0=[], NT=None, r=None, ops=[], infoFields=[])¶: An linear population growth model that evolves a population from size N0 to NT for T generations with r*N0 individuals added at each generation. N0, NT and r can be a list of population sizes or growth rates for multiple subpopulations. The initial population will be resized to N0 (split if necessary). Zero or negative growth rates are allowed. The model will automatically determine T, r or NT if one of them is unspecified. If all of them are specified, NT is intepretted as carrying capacity of the model, namely the population will keep contant after it reaches size NT. Optionally, one or more operators (e.g. a migrator) ops can be applied to population.

plot(filename='', title='', initSize=[])¶: Evolve a haploid population using a RandomSelection mating scheme using the demographic model. Print population size changes duringe evolution. An initial population size could be specified using parameter initSize for a demographic model with dynamic initial population size. If a filename is specified and if matplotlib is available, this function draws a figure to depict the demographic model and save it to filename. An optional title could be specified to the figure. Note that this function can not be plot demographic models that works for particular mating schemes (e.g. genotype dependent).

class MultiStageModel¶

class simuPOP.demography.MultiStageModel¶

A multi-stage demographic model that connects a number of demographic models.

MultiStageModel(models, ops=[], infoFields=[])¶: An multi-stage demographic model that connects specified demographic models models. It applies a model to the population until it reaches num_gens of the model, or if the model returns []. One or more operators could be specified, which will be applied before a demographic model is applied. Note that the last model will be ignored if it lasts 0 generation.

plot(filename='', title='', initSize=[])¶: Evolve a haploid population using a RandomSelection mating scheme using the demographic model. Print population size changes duringe evolution. An initial population size could be specified using parameter initSize for a demographic model with dynamic initial population size. If a filename is specified and if matplotlib is available, this function draws a figure to depict the demographic model and save it to filename. An optional title could be specified to the figure. Note that this function can not be plot demographic models that works for particular mating schemes (e.g. genotype dependent).

class OutOfAfricaModel¶

class simuPOP.demography.OutOfAfricaModel¶

A dempgraphic model for the CHB, CEU, and YRI populations, as defined in Gutenkunst 2009, Plos Genetics. The model is depicted in Figure 2, and the default parameters are listed in Table 1 of this paper.

OutOfAfricaModel(T0, N_A=7300, N_AF=12300, N_B=2100, N_EU0=1000, r_EU=0.004, N_AS0=510, r_AS=0.0055, m_AF_B=0.00025, m_AF_EU=3e-05, m_AF_AS=1.9e-05, m_EU_AS=9.6e-05, T_AF=8800, T_B=5600, T_EU_AS=848, ops=[], infoFields=[], outcome=['AF', 'EU', 'AS'], scale=1)¶

Counting backward in time, this model evolves a population for T0 generations (required parameter). The ancient population A started at size N_A and expanded at T_AF generations from now, to pop AF with size N_AF. Pop B split from pop AF at T_B generations from now, with size N_B; Pop AF remains as N_AF individuals. Pop EU and AS split from pop B at T_EU_AS generations from now; with size N_EU0 individuals and N_ASO individuals, respectively. Pop EU grew exponentially with rate r_EU; Pop AS grew exponentially with rate r_AS. The YRI, CEU and CHB samples are drawn from AF, EU and AS populations respectively. Additional operators could be added to ops. Information fields required by these operators should be passed to infoFields. If a scaling factor scale is specified, all population sizes and generation numbers will be divided by a factor of scale. This demographic model by default returns all populations (AF, EU, AS) but you can choose to keep only selected subpopulations using parameter outcome (e.g. outcome=['EU', 'AS']).

This model merges all subpopulations if it is applied to an initial population with multiple subpopulation.

plot(filename='', title='', initSize=[])¶: Evolve a haploid population using a RandomSelection mating scheme using the demographic model. Print population size changes duringe evolution. An initial population size could be specified using parameter initSize for a demographic model with dynamic initial population size. If a filename is specified and if matplotlib is available, this function draws a figure to depict the demographic model and save it to filename. An optional title could be specified to the figure. Note that this function can not be plot demographic models that works for particular mating schemes (e.g. genotype dependent).

class SettlementOfNewWorldModel¶

class simuPOP.demography.SettlementOfNewWorldModel¶

A dempgraphic model for settlement of the new world of Americans, as defined in Gutenkunst 2009, Plos Genetics. The model is depicted in Figure 3, and the default parameters are listed in Table 2 of this paper.

SettlementOfNewWorldModel(T0, N_A=7300, N_AF=12300, N_B=2100, N_EU0=1500, r_EU=0.0023, N_AS0=590, r_AS=0.0037, N_MX0=800, r_MX=0.005, m_AF_B=0.00025, m_AF_EU=3e-05, m_AF_AS=1.9e-05, m_EU_AS=1.35e-05, T_AF=8800, T_B=5600, T_EU_AS=1056, T_MX=864, f_MX=0.48, ops=[], infoFields=[], outcome='MXL', scale=1)¶

Counting backward in time, this model evolves a population for T0 generations. The ancient population A started at size N_A and expanded at T_AF generations from now, to pop AF with size N_AF. Pop B split from pop AF at T_B generations from now, with size N_B; Pop AF remains as N_AF individuals. Pop EU and AS split from pop B at T_EU_AS generations from now; with size N_EU0 individuals and N_ASO individuals, respectively. Pop EU grew exponentially with final population size N_EU; Pop AS grew exponentially with final populaiton size N_AS. Pop MX split from pop AS at T_MX generations from now with size N_MX0, grew exponentially to final size N_MX. Migrations are allowed between populations with migration rates m_AF_B, m_EU_AS, m_AF_EU, and m_AF_AS. At the end of the evolution, the AF and CHB populations are removed, and the EU and MX populations are merged with f_MX proportion for MX. The Mexican American<F19> sample could be sampled from the last single population. Additional operators could be added to ops. Information fields required by these operators should be passed to infoFields. If a scaling factor scale is specified, all population sizes and generation numbers will be divided by a factor of scale. This demographic model by default only returns the mixed Mexican America model (outputcom='MXL') but you can specify any combination of AF, EU, AS, MX and MXL.

This model merges all subpopulations if it is applied to an initial population with multiple subpopulation.

plot(filename='', title='', initSize=[])¶: Evolve a haploid population using a RandomSelection mating scheme using the demographic model. Print population size changes duringe evolution. An initial population size could be specified using parameter initSize for a demographic model with dynamic initial population size. If a filename is specified and if matplotlib is available, this function draws a figure to depict the demographic model and save it to filename. An optional title could be specified to the figure. Note that this function can not be plot demographic models that works for particular mating schemes (e.g. genotype dependent).

class CosiModel¶

class simuPOP.demography.CosiModel¶

A dempgraphic model for Africa, Asia and Europe, as described in Schaffner et al, Genome Research, 2005, and implemented in the coalescent simulator cosi.

CosiModel(T0, N_A=12500, N_AF=24000, N_OoA=7700, N_AF1=100000, N_AS1=100000, N_EU1=100000, T_AF=17000, T_OoA=3500, T_EU_AS=2000, T_AS_exp=400, T_EU_exp=350, T_AF_exp=200, F_OoA=0.085, F_AS=0.067, F_EU=0.02, F_AF=0.02, m_AF_EU=3.2e-05, m_AF_AS=8e-06, ops=[], infoFields=[], scale=1)¶

Counting backward in time, this model evolves a population for a total of T0 generations. The ancient population Ancestral started at size N_Ancestral and expanded at T_AF generations from now, to pop AF with size N_AF. The Out of Africa population split from the AF population at T_OoA generations ago. The OoA population split into two subpopulations AS and EU but keep the same size. At the generations of T_EU_exp, T_AS_exp, and T_AF_exp ago, three populations expanded to modern population sizes of N_AF1, N_AS1 and N_EU1 exponentially, respectively. Migrations are allowed between AF and EU populations with rate m_AF_EU, and between AF and AS with rate m_AF_AS.

Four bottlenecks happens in the AF, OoA, EU and AS populations. They are supposed to happen 200 generations after population split and last for 200 generations. The intensity is parameterized in F, which is number of generations devided by twice the effective size during bottleneck. So the bottleneck size is 100/F.

This model merges all subpopulations if it is applied to a population with multiple subpopulation. Although parameters are configurable, we assume the order of events so dramatically changes of parameters might need to errors. If a scaling factor scale is specified, all population sizes and generation numbers will be divided by, and migration rates will be multiplied by a factor of scale.

plot(filename='', title='', initSize=[])¶: Evolve a haploid population using a RandomSelection mating scheme using the demographic model. Print population size changes duringe evolution. An initial population size could be specified using parameter initSize for a demographic model with dynamic initial population size. If a filename is specified and if matplotlib is available, this function draws a figure to depict the demographic model and save it to filename. An optional title could be specified to the figure. Note that this function can not be plot demographic models that works for particular mating schemes (e.g. genotype dependent).

Module `simuPOP.demography`¶

Function migrIslandRates¶

Function migrHierarchicalIslandRates¶

Function migrSteppingStoneRates¶

Function migrtwoDSteppingStoneRates¶

class EventBasedModel¶

class DemographicEvent¶

class ExpansionEvent¶

class ResizeEvent¶

class SplitEvent¶

class MergeEvent¶

class AdmixtureEvent¶

class InstantChangeModel¶

class ExponentialGrowthModel¶

class LinearGrowthModel¶

class MultiStageModel¶

class OutOfAfricaModel¶

class SettlementOfNewWorldModel¶

class CosiModel¶

simuPOP

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Related Topics

Module simuPOP.demography¶

Function migrIslandRates¶

Function migrHierarchicalIslandRates¶

Function migrSteppingStoneRates¶

Function migrtwoDSteppingStoneRates¶

class EventBasedModel¶

class DemographicEvent¶

class ExpansionEvent¶

class ResizeEvent¶

class SplitEvent¶

class MergeEvent¶

class AdmixtureEvent¶

class InstantChangeModel¶

class ExponentialGrowthModel¶

class LinearGrowthModel¶

class MultiStageModel¶

class OutOfAfricaModel¶

class SettlementOfNewWorldModel¶

class CosiModel¶

Module `simuPOP.demography`¶