FvU

Fused versus Unfused - Modelling the behaviour of chromosomal clines with sexually antagonistic selection acting

Veltsos et al. 2008 modelled two things. (1) the selection conditions for which a neo-X/neo-Y sex determination system can become fixed in a population with X0-system, and (2) which conditions favour the spread of the neo-sex chromosome system into other populations. This repo recapitulates and extends (2).

Files

###FvU3D_sizelayer.py Models hybrid zone with directional gene flow due to a population size gradient.

####Usage python FvU3D.py <sm> <dm> <sf> <df> <sh> <sd> <sc> <disp> <grad> <run no>
EXAMPLE: python FvU3D_sizelayer.py .01 1 .01 1 0 0 0 .03 4 1
This will use a gradient of 6% effectively stopping the clines' forward-movement. The parameters are:
sm (selection against the Y in males),
dm (dominance of the Y in males),
sf (selection against the Y in males),
df (dominance of the Y in males),
sh (selection against heterozygote females, heterozygote disadvantage),
sd (dosage compensation),
sc (sex chromosome co-adaption),
disp (fraction of a deme that disperse to each direction i.e. the actual dispersal is dispx4),
grad (population size gradient to be used; possible options are 0-8 for speepnesses of 0, 1, 3, 5, 6, 7, 9, 11, and 13%), and
run (a number that will be part of the output file names)

####Outputs

1. one tab-delimited TXT file with GLM parameters (intercept, slope, and centre of the Y cline plus intercept, slope, and centre of the fused-X cline),
2. every ten generations: one GZ-compressed pickle file of the genotype dictionary, and
3. every ten generations: one GZ-compressed TXT table with hits and misses for F and Y (can be imported into R to visualise it with rgl or to do other funny things)
   The standard array shape is 10x100 populations with cline inflection points between 60 and 61.

####Requirements

Requires the python libraries numpy, pickle, and statsmodels.

###FvU3D_sizelayer_wind.py

Very similar to FvU3D_sizelayer.py, but there is no population size gradient. The simulation will be run on a 10x120 array with 40 individuals in each generation. Directional gene flow is implemented as a fraction (dispmod) that is taken away from rightward dispersal and added to leftward dispersal.

####Usage

python FvU3D.py <sm> <dm> <sf> <df> <sh> <sd> <sc> <disp> <dispmod> <run no>
EXAMPLE: python FvU3D_sizelayer.py .01 1 .01 1 0 0 0 .03 4 1
This will use a gradient of 6% effectively stopping the clines' forward-movement. The parameters are:
sm (selection against the Y in males),
dm (dominance of the Y in males),
sf (selection against the Y in males),
df (dominance of the Y in males),
sh (selection against heterozygote females, heterozygote disadvantage),
sd (dosage compensation),
sc (sex chromosome co-adaption),
disp (fraction of a deme that disperse to each direction i.e. the actual dispersal is dispx4),
dispmod (percentage that is removed from rightward dispersal and added to leftward dispersal), and
run (a number that will be part of the output file names)

####Outputs

1. one tab-delimited TXT file with GLM parameters (intercept, slope, and centre of the Y cline plus intercept, slope, and centre of the fused-X cline),
2. every ten generations: one GZ-compressed pickle file of the genotype dictionary, and
3. every ten generations: one GZ-compressed TXT table with hits and misses for F and Y (can be imported into R to visualise it with rgl or to do other funny things)
   The standard array shape is 10x100 populations with cline inflection points between 60 and 61.

####Requirements

Requires the python libraries numpy, pickle, and statsmodels.