GPASDiscrimination: Execute the GPAS algorithm for discrimination

In RFreak: R/FrEAK interface

Description

Working on categorical data with binary response, the algorithm searches for multi-valued logic expressions in disjunctive normal form discriminating between response 0 and response 1. The algorithm is intended for genetic association studies on SNP data.

Usage

GPASDiscrimination(resp.train, preds.train, resp.test=NULL,
  preds.test=NULL, runs = 1, generations = 10000)

Arguments

resp.train	Vector with the response variables of the training data set
preds.train	Matrix or data frame with the predictors of the training data set
resp.test	Optional vector with the response variables of the test data set
preds.test	Optional matrix or data frame with the predictors of the test data set
runs	Number of independent runs of GPAS
generations	Number of generations after which the algorithm will be stopped

Value

Returns an object of class GPAS with a data.frame in its slot summary containing information about the last population of the executed discrimination runs. For each individual in the last population the following information is contained:

data set	Either 'training' or 'test' or omitted
run	The run the individual was found in
generation	The generation the individual was created in
objective value 1	Correctly predicted cases
objective value 2	Correctly predicted controls
objective value 3	Length of the individual
individual	A string representation of the individual

Author(s)

Robin Nunkesser [e-mail]

References

R. Nunkesser, T. Bernholt, H. Schwender, K. Ickstadt, and I. Wegener (2007). Detecting High-Order Interactions of Single Nucleotide Polymorphisms Using Genetic Programming. Bioinformatics, 23, 3280-3288.

See Also

"GPAS", GPASInteractions

Examples

# load example data
data(data.logicfs)

# execute GPAS to discriminate between cases and controls
GPASDiscrimination(cl.logicfs,data.logicfs,runs=1,generations=1000)

RFreak documentation built on May 1, 2019, 10:53 p.m.