DFP-package {DFP} | R Documentation |
This package provides a supervised technique able to identify differentially expressed genes, based on the construction of Fuzzy Patterns (FPs). The Fuzzy Patterns are built by means of applying 3 Membership Functions to discretized gene expression values.
Package: | DFP |
Type: | Package |
Version: | 1.0 |
Date: | 2008-07-03 |
License: | GPL-2 |
The main functionality of the package is provided by the discriminantFuzzyPattern
function, which works in a 4-step process:
Additional data classes: ExpressionSet
, AnnotatedDataFrame
.
Rodrigo Alvarez-Gonzalez
Daniel Glez-Pena
Fernando Diaz
Florentino Fdez-Riverola
Maintainer: Rodrigo Alvarez-Gonzalez <rodrigo.djv@uvigo.es>
F. Diaz; F. Fdez-Riverola; D. Glez-Pena; J.M. Corchado. Using Fuzzy Patterns for Gene Selection and Data Reduction on Microarray Data. 7th International Conference on Intelligent Data Engineering and Automated Learning: IDEAL 2006, (2006) pp. 1095-1102
######################################### ############ Get sample data ############ ######################################### library(DFP) data(rmadataset) ######################################### # Filter the most representative genes # ######################################### res <- discriminantFuzzyPattern(rmadataset) ######################################### ###### Different result displays ######## ######################################### plotMembershipFunctions(rmadataset, res$membership.functions, featureNames(rmadataset)[1:2]) showDiscreteValues(res$discrete.values, featureNames(rmadataset)[1:10], c("healthy", "AML-inv")) showFuzzyPatterns(res$fuzzy.patterns, "healthy")[21:50] plotDiscriminantFuzzyPattern(res$discriminant.fuzzy.pattern)