RFreak (version 0.3-0)

GPASDiscrimination: Execute the GPAS algorithm for discrimination

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

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)