classic

• Introduction
  • Flow Diagram
• Overview of Parameters
• Details to Parameters
  • --fu
    • --fu decr
  • --fw
    • --fw decr
  • --fv
    • --fv incr
  • --genome
  • --N
  • --rr
  • --nsmodel
  • --basepop

Introduction

Flow Diagram

At each generation Invade-cluster proceeds in the following order

Overview of Parameters

Following an overview of the parameters. Detailed descriptions for more complex parameters are provided in the next section

** Mandatory parameters**

• --genome: specify the properties of the simulated genome (for details see next section)
• --fu the function of the transposition rate
• --fw the function of the fitness w
• --N: the population size (in diploids)
• --gen: the number of generations to simulate
• --basepop: specify the distribution of insertions in the starting population (for details see next section)

Optional parameters

• --rep the number of replicate runs to use
• --rr the recomination rate (for details see next section)
• --cluster the size of piRNA clusters (for details see next section)
• --fv the function of excisions
• --x the negative effect of a TE insertion; default=0.0
• --steps store the output each --steps generation
• --nsmodel negative selection model (for details see next section)
• --seed a seed for the random number generator (allows reproducing previous results); default = current time
• --min-w minimum fitness; a population will die out if fitness drops below --min-w
• --detailed-output-file: a file for detailed output such as the SFS of TEs, or the insertion counts for every individual in the population
• --sim-id simulation id; maybe useful for plotting the results in R with ggplot2; especially if multiple independent simulations were performed
• --tally-file optional output of the number of TE insertions per diploid individual;
• --sfs-file the site frequency spectrum
• --mhp-file optional output of the position and population frequency of TE insertions; allows to generate Manhattanplots about the landscape of TE insertions
• --silent do not show log (just show output) actually recommended
• --help display help

Details to Parameters

--fu

function (f) of the transposition rate (u)

• '--fu const:0.05' use constant transposition rate of 0.05
• '--fu 0.05' the same as '--fu const:0.05'
• '--fu decr:u0=0.05,k=0.1' the transposition rate (un) decreases with TE copy numbers (n)
• default: will assume '--fu const:0.0'

--fu decr

The transposition rate (un) decreases with the number of TE insertions per diploid individual (n).
The following graph shows the relation between the initial transpositon rate (u0), the number of TE insertions (n), the parameter k and the resulting transposition rate (un).
The following equation is used un=u0/(1+kn)
The equation is from Charlesworth and Charlesworth 1983

--fw

function (f) of the fitness (w)

• '--fw const:0.05' use constant negative selection coefficient of a TE insertion x=0.05; The fitness can be computed as w=1-xn, where n is the number of insertions)
• '--fw 0.05' the same as '--fw const:0.05'
• '--fw decr:x=0.05,t=1.4' the fitness decreases exponentially with the number of TE insertions

--fw decr

The fitness (wn) decreases with the number of insertions (n) and given some negative effect of a TE insertion (here x=0.01).
The exponential parameter t gives the steepness of the fitness decline. Note that an exponential value t=1 corresponds to the constant fitness decrease (e.g. const:0.05 with x=0.05).
According to Charlesworth and Charlesworth 1983 the following equation is used: wn=1-xn^t

--fv

function (f) of the excision rate (v)

• '--fv const:0.05' use constant excision rate of 0.05
• '--fv 0.05' the same as '--fv const:0.05'
• '--fv incr:v0=0.1,k=0.1' the excision rate (vn) increases with TE copy numbers (n)
• default: will use '--fv const:0.0'

--fv incr

The excision rate (vn) increases with the number of TE insertions per diploid individual (n).
The following graph shows the relation between the target excision rate (v0), the number of TE insertions (n), the parameter k and the resulting excision rate (vn).
The following equation is used vn=v0((kn)/(1+kn))
The equation is inspired by Charlesworth and Charlesworth 1983, it is however not explicitely contained in this publication (in fact no equation for an increasing excision rate is provided).

--genome

Specify the genome, following some examples

• '--genome Mb:1' simulate a single chromosome of size 1 million base pairs
• '--genome Mb:1,2,1,4' simulate four chromosomes with sizes 1, 2, 1 and 4 million base pairs
• '--genome kb:34,15' simulate two chromosomes with size 34 and 15 thousand base pairs
• '--genome bp:1000,5000' simulate two chromosomes with size 1000 and 5000 base pairs
• '--genome 1000,2000' simulate two chromosomes with size 1000 and 2000

Note the unit is optional, if not provided a default unit of bp is assumed

--N

Specify the population size; This is a mandatory parameter. Following some examples

• '--N 500' a population size of 500 will be used
• '--N 0:500, starting at generation size 0 a population size of 500 will be used (same as '--N 500'); generation zero is the base population
• '--N 0:500,1000:2000' from generation 0 to 1000 a population size of 500 will be used; Starting at generation 1000 a population size of 2000 will be used
• '--N 0:300,40:500,100:1000' from generation 0 to 40 a population size of 40 will be used; from generation 40 to100 a population size of 500 will be used; starting at generation 100 a population size of 1000 will be used
• --N 40:500,100:1000,0:300,' from generation 1 to 40 a population size of 40 will be used; from generation 40 to100 a population size of 500 will be used; starting at generation 100 a population size of 1000 will be used;

Note the order of the generations is not important (compare with prev. example)

Note a population size for the base population must be provided

--rr

Provide the recombination rate. This is an optional parameter. A default recombination rate of zero will be used when not provided.

Following some examples

• '--rr lambda:2' simulate a mean number of cross overs of 2 for one chromosome
• '--rr lambda:2,3,2,1' simulate a mean number of cross overs of 2 for the first chromosome, 3 for the second, 2, for the fourth and 1 for the fifth.
• '--rr cm_mb:4' simulate a cross over rate of 4 centiMorgan per megabase pair for the first chromosome
• '--rr cm_mb:4,2,10' simulate a cross over rate of 4 centiMorgan per megabase pair for the first chromosome, 2 for the second and 10 for the third

Note the number recombination values must match the number of chromosomes
Note if this parameter is not provided a recombination rate of 0.0 will be used for all chromosomes

--nsmodel

Model of negative selection against TEs. Three possible models are supported

• '--nsmodel add' additive effects; each insertions contributes equally to fitness. Consequently homozygous insertions count as two.
• '--nsmodel het' only heterozygous insertions contribute negatively to fitness. This is justified by ectopic recombination
• '--nsmodel rec' recessive model; only homozygous insertions contribute to fitness; Justified by haplosufficiency

--basepop

Define insertions in the starting population. Following some examples

• '--basepop seg:50' will simulate 50 segregating insertions with random positions; All insertion will have the population frequency of 1/2N (unless due to chance two or more insertions occur at the same site)
• '--basepop fix:10' will simulate 10 fixed insertions with random positions