readCSV: Creates an ExpressionSet with an AnnotatedDataFrame from CSV...

Description Usage Arguments Value Author(s) References Examples

View source: R/DFP.R

Description

This function creates an ExpressionSet with an AnnotatedDataFrame. To do this, it requires two CSV files in a predefined format:

  1. exprsData’ with the expression values of genes (in rows) of different samples (in columns).

  2. pData’ with the samples (in columns) and the metadata ‘class’ (the most important for the algorithm discriminantFuzzyPattern), ‘age’ and ‘sex’.

Usage

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readCSV(fileExprs, filePhenodata)

Arguments

fileExprs

The path to the exprsData file.

filePhenodata

The path to the pData file.

Value

An ExpressionSet object with an AnnotatedDataFrame storing ‘class’, ‘age’ and ‘sex’ information.

Author(s)

Rodrigo Alvarez-Gonzalez
Daniel Glez-Pena
Fernando Diaz
Florentino Fdez-Riverola
Maintainer: Rodrigo Alvarez-Gonzalez <[email protected]>

References

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

Examples

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dataDir <- system.file("extdata", package="DFP"); dataDir
fileExprs <- file.path(dataDir, "exprsData.csv"); fileExprs
filePhenodata <- file.path(dataDir, "pData.csv"); filePhenodata
rmadataset <- readCSV(fileExprs, filePhenodata); rmadataset
pData(phenoData(rmadataset))
exprs(rmadataset)[1:10,1:5]

DFP documentation built on May 2, 2018, 4:15 a.m.