algogen

Tries to optimize the maximum multipoint loglikelihood using a dedicated genetic algorithm.

Synopsis :

The CarthaGene algogen command is invoked as either one of :

• lelacommande Options
• lelacommande NbGen NbMap SelType ProbaCross ProbaMut EvolFitn

Description :

The genetic algorithm tries to optimize the loglikelihood of orders using a simulation of mating, mutation and selection by fitness. The initial population is defined by the best maps stored in the heap or from generated maps.

As the algorithm runs, ``+'' are printed on a generation such that a map is found that improves over the best map known.

Arguments :

• Options : -u to obtain the synopsys of the normal use, -h to print a one line description, -H to print a short help.
• The Nbgen argument correspond to the number of generations simulated.
• The NbMap argument correspond to the size of the population. If NbMap is set to 0, the command uses the heap to initialize the first generation population.
• The SelType argument specifies the type of selection used (0 for the roulette wheel, 1 for the stochastic remainder without replacement).
• The ProbaCross argument correspond to the probability of crossing-over. A typical value is 60 %.
• The ProbaMut argument correspond to the probability of mutation. A typical value is 5 to 10 %.
• The EvolFitn is a flag to set the evolutive fitness (0 or 1) which mean that selection becomes harder and harder with generations.

Returns :

nothing, all maps explored are candidate for being stored in the heap.

Example :

   CarthaGene version 1.2-LKH, Copyright (c) 1997-2010 (INRA).

   CarthaGene comes with ABSOLUTELY NO WARRANTY.
   CarthaGene is free software. You are welcome to redistribute it,
   under certain conditions. See the License file for information.

Type 'help' for help.

# we load a dataset
CG> dsload Data/rh.cg
{1 haploid RH 53 118 /home/tschiex/Dev/carthagene/doc/user/exemple/Data/rh.cg}
# perform linkage group detection (output omitted)
CG> group 0.3 3
...
# we select the group 10
CG> mrkselset [groupget 10]

# put one (stupid) map in the heap using the 'sem' command
CG> sem

Map -1 : log10-likelihood =  -161.87
-------:
 Set : Marker List ...
   1 : G5 G18 G17 G14 G16 G13 G12 G6 G7

# launch the 'algogen' command
CG> algogen 10 8 1 0.6 0.1 1
+
-
-
-
-
-
-
-
-
-

# check the reliability of the result with a large flip
CG> flips 9 0 0

Single Flip(window size : 9, threshold : 0.00).


Map -1 : log10-likelihood =  -141.81
-------:
 Set : Marker List ...
   1 : G7 G12 G13 G16 G6 G5 G17 G18 G14


 2 2 2 3 2 1 3 3 2  log10
 1 6 7 0 0 9 1 2 8   -141.81
[8 7 6 5 - 3 2 1 0]      0.00


# the map was optimal

See also:

• greedy (2.6.8)
• annealing (2.6.7)
• flips (2.6.4)
• polish (2.6.5)