geneCoverage.BigBang: Computes the fraction of genes present in the top-rank from...

In galgo: Genetic Algorithms for Multivariate Statistical Models from Large-Scale Functional Genomics Data

Description

Computes the fraction of genes present in the top-rank from the total genes present in chromosomes.

Usage

## S3 method for class 'BigBang'
geneCoverage(o, filter="none", subset=TRUE, chromosomes=NULL, ...)

Arguments

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.

Value

A vector with the fraction of genes present in each rank from the total genes present in chromosomes.

Author(s)

Victor Trevino. Francesco Falciani Group. University of Birmingham, U.K. http://www.bip.bham.ac.uk/bioinf

References

Goldberg, David E. 1989 Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Pub. Co. ISBN: 0201157675

See Also

For more information see BigBang. *plot().

Examples

## Not run: 
   #bb is a BigBang object
   gc <- geneCoverage(bb)
   gc
   
## End(Not run)
 

galgo documentation built on May 2, 2019, 4:20 a.m.