Populations

A population is a collection of

either a lattice<:RealLattice if the model is spatial (see lattices), or a dummy placeholder NoLattice if it is not.
a phylogenetic tree, which is a directed graph where the root(s) represent the wild type(s).
metadata about the population and its genetics. See Metadata.
the time the state has been evolved for by invoking dynamics on it.

They are of type Population.

It is normally not required to manipulate metadata, phylogeny or lattice directly. Convenient methods to manipulate state are provided.

julia>     state, _ = uniform(CubicLattice, 32; g=0)(CubicLattice{Int64, Array{Int64, 3}}
0	genotypes
0	population, nothing)
julia>     # fails because the new genotype is yet unknown
           state[16,16,16] = 1ERROR: ArgumentError: Genotype 1 is not know. Use push!(::Population, 1) first.
julia>     # make it known first
           # last paremeter is the parental genotype
           # because there is none yet, set it to `nothing`
           add_genotype!(state, 1, nothing)1
julia>     state[16,16,16] = 1;
julia>     state.meta1-element MetaData{Int64}:
 (genotype = 1, npop = 1, fitness = 1.0, snps = nothing, age = (0, 0.0))
julia>     state[15:17,15:17,15:17]3×3×3 Array{Int64, 3}:
[:, :, 1] =
 0  0  0
 0  0  0
 0  0  0

[:, :, 2] =
 0  0  0
 0  1  0
 0  0  0

[:, :, 3] =
 0  0  0
 0  0  0
 0  0  0
julia>     push!(state, 2)2
julia>     state[1:size(state,1), 1, 1] .= 2;
julia>     state.meta2-element MetaData{Int64}:
 (genotype = 1, npop = 1, fitness = 1.0, snps = nothing, age = (0, 0.0))
 (genotype = 2, npop = 33, fitness = 1.0, snps = nothing, age = (0, 0.0))

Convenience constructors

A handful of methods to generate common geometries are provided. They return a tuple (population,auxilliary). The latter holds information that might be nice to have. It is often nothing, but for example spherer returns a vector with all indices contained in the ball.

GrowthDynamics.Populations.uniform — Function

uniform(T, L; g=0, a=1.0)

A population on a lattice of type T with linear extension L, filled with genotype g.

Return (population, nothing).

Example

julia> uniform(HexagonalLattice, 128; g=1)
(HexagonalLattice{Int64, Matrix{Int64}}
1	genotypes
16641	population, nothing)

source

GrowthDynamics.Populations.spheref — Function

spheref(T, L::Int; r = 0, g1=0, g2=1) where LT<:Lattices.RealLattice

Fill lattice of type T (e.g CubicLattice) with genotype g1 and put a (L2-)ball with genotype g2 that occupies approx. a fraction f of the lattice at the center.

Return (population, idx_ball) with idx_ball being the indices of sites within the ball.

source

GrowthDynamics.Populations.spherer — Function

spherer(T, L::Int; r = 0, g1=0, g2=1) where LT<:Lattices.RealLattice

Fill lattice of type T (e.g CubicLattice) with genotype g1 and put a (L2-)ball of approx. radius r with genotype g2 at the center.

Return (population, idx_ball) with idx_ball being the indices of sites within the ball.

source

GrowthDynamics.Populations.single_center — Function

single_center(T, L; g1=1, g2=2)

A single cell of genotype g2 at the midpoint of a lattice of type T filled with g1.

Return (population, midpoint::Index)

source

GrowthDynamics.Populations.half_space — Function

half_space(T, L; g1=1, g2=2)

A population of genotype g1 on a lattice of type T. Fill the last dimension with g2 up to fraction f

Return (population, fill_to) with fill_to defined as state[:,..., 1:fill_to] == g2 and state[:,..., fill_to+1:end] == g1.

Example

julia> using GrowthDynamics.Populations

julia> state = half_space(CubicLattice, 32, f=1/4, g1=1, g2=2)[1]
CubicLattice{Int64, Array{Int64, 3}}
2	genotypes
35937	population

julia> state.meta
2-element MetaData{Int64}:
 (genotype = 1, npop = 27225, fitness = 1.0, snps = nothing, age = (0, 0.0))
 (genotype = 2, npop = 8712, fitness = 1.0, snps = nothing, age = (0, 0.0))

source

GrowthDynamics.Populations.sphere_with_single_mutant_on_outer_shell — Function

sphere_with_single_mutant_on_outer_shell(T, L::Int; r, s=1.0)

A lattice of type T (e.g CubicLattice) with an (L2-)ball of genotype 1 and radius r at the center. One random site on the outermost shell is populated with genotype 2 that has fitness s.

Return (population, (idx_shell, idx_mutant)) with idx_shell being the indices of the outer shell, and idx_mutant the index of the mutant genotype.

source

GrowthDynamics.Populations.sphere_with_diverse_outer_shell — Function

sphere_with_diverse_outer_shell(T, L; r)

A lattice of type T (e.g CubicLattice) with an (L2-)ball of genotype 1 and radius r at the center. Each site on the outermost shell is populated consecutively with a different genotype, starting from 2.

Return (population, idx_shell) with idx_shell being the indices of the outer ("diverse") shell.

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An initial population without spatial structure can be constructed with

GrowthDynamics.Populations.nolattice_state — Function

nolattice_state()

Model without spatial structure. Populated with one individual of genotype 1 with fitness 1.0.

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API

Manipulating genotypes

GrowthDynamics.Populations.Population — Type

Population{G, T}

Represents a population on a lattice of type T with genotypes of data type G.

Fields

lattice<:Lattices.AbstractLattice
phylogeny: directed graph recording the ancestry of genotypes
meta::MetaData: metadata such as fitnesses, mutations, etc. See MetaData.
t::Int: age in timesteps
treal::Float64: age in "real" time.
observables: dictionary to store observables in

source

GrowthDynamics.Populations.add_genotype! — Function

add_genotype!(S::Population, G, parent)

Add genotype G to the population and connect it to parent in the phylogeny. G is either a genotype or a full MetaDatum. parent defaults to the first genotype, i.e. the root of the phylogenetic tree. If parent=nothing, the genotype will not be connected to the tree.

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GrowthDynamics.Populations.remove_genotype! — Function

remove_genotype!(S::Population, g; bridge=true)

Remove genotype from the population. Discards it from meta data, prunes it from the phylogeny, and sets all corresponding sites of the lattice to zero.

If bridge=true (default), the gap in the phylogeny is bridged with new edges.

Throw an exception if the requested genotype does not exist.

Return true if successful, else false.

source

Base.push! — Function

Add a new unconnected genotype to a Population.

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Methods to add mutations

GrowthDynamics.Populations.add_snps! — Function

add_snps!(state::Population, g, μ)

Randomize and add mutations to genotype g, or replace them. μ is the genome wide mutation rate (Poisson) or mutation count (fixed).

Note: allow_multiple is much faster if the number of mutations already present is large.

Keyword arguments

L=10^9: length of the genome
allow_multiple=false: allow for a site to mutate more than once.
kind=:poisson: either :poisson or :fixed
replace=false: replace existing SNPs.

source

add_snps!(state::Population, g, v::Vector{Int})

Add mutations v to genotype g. No checks for duplications are performed.

Return a vector of all mutations.

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Missing docstring.

Missing docstring for annotate_snps!. Check Documenter's build log for details.

Missing docstring.

Missing docstring for annotate_lineage!. Check Documenter's build log for details.