| geneCoverage.BigBang {galgo} | R Documentation |
Computes the fraction of genes present in the top-rank from the total genes present in chromosomes.
## S3 method for class 'BigBang': geneCoverage(o, filter="none", subset=TRUE, chromosomes=NULL, ...)
filter |
The BigBang object can save information about solutions that did not reach the goalFitness. filter=="solutions" ensures that only chromosomes that reach the goalFitness are considered. fitlter=="none" take all chromosomes. filter=="nosolutions" consider only no-solutions (for comparative purposes). |
subset |
Second level of filter. subset can be a vector specifying which filtered chromosomes are used. It can be a logical vector or a numeric vector (indexes in order given by $bestChromosomes in BigBang object variable). If it is a numeric vector length one, a positive value means take those top chromosomes sorted by fitness, a negative value take those at bottom. |
chromosomes |
The chromosomes to process. The default is using filter and subset to extract the chromosomes from the BigBang object. |
A vector with the fraction of genes present in each rank from the total genes present in chromosomes.
Victor Trevino. Francesco Falciani Group. University of Birmingham, U.K. http://www.bip.bham.ac.uk/bioinf
Goldberg, David E. 1989 Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Pub. Co. ISBN: 0201157675
For more information see BigBang.
*plot().
#bb is a BigBang object gc <- geneCoverage(bb) gc