Learn R Programming

DFP (version 1.30.0)

Gene Selection

Description

This package provides a supervised technique able to identify differentially expressed genes, based on the construction of \emph{Fuzzy Patterns} (FPs). The Fuzzy Patterns are built by means of applying 3 Membership Functions to discretized gene expression values.

Copy Link

Version

Version

1.30.0

License

GPL-2

Maintainer

Rodrigo AlvarezGlez

Last Published

February 15th, 2017

Functions in DFP (1.30.0)

ExpressionLevel-class

Class "ExpressionLevel"
discriminantFuzzyPattern

Discriminant Fuzzy Pattern to filter genes
calculateFuzzyPatterns

Calculates a Fuzzy Pattern for each category of the samples
show-methods

Prints the slots (attributes) of an ExpressionLevel object
LowExpressionLevel-class

Class "LowExpressionLevel"
showFuzzyPatterns

Plots the Fuzzy Patterns corresponding to a class
readCSV

Creates an ExpressionSet with an AnnotatedDataFrame from CSV files
calculateDiscriminantFuzzyPattern

Calculates the Discriminant Fuzzy Pattern to select significative genes
DFP-package

DFP Package Overview
discretizeExpressionValues

Function to discretize gene expression data
showDiscreteValues

Prints the labels to which the algorithm converts the gene expression values
DFP-internal

Internal DFP objects
calculateMembershipFunctions

Calculates Membership Functions
HighExpressionLevel-class

Class "HighExpressionLevel"
rmadataset

A sample ExpressionSet object
plotDiscriminantFuzzyPattern

Plots the Discriminant Fuzzy Pattern of the relevant genes
plotMembershipFunctions

Plots the Membership Functions (Low, Medium, High) used to discretize gene expression values
MediumExpressionLevel-class

Class "MediumExpressionLevel"