Microarray data classification

Quick start

Installation

source("http://bioconductor.org/biocLite.R")
biocLite("limma")
library(devtools)
install_github("uarray", username="b3aver")
library(uarray)

Training

trainingsetFN <- "data/trainingset.csv"
## or for a dataset provided with the package
## trainingsetFN <- system.file("extdata", "Brain_Cancer.csv", package="uarray")
trainingset <- read(trainingsetFN)
filteredTS <- gfilter(trainingset)
discretizedTS <- gdiscretize(filteredTS)
classificationModel <- train(discretizedTS$dataset, discretizedTS$intervals)

Classification

newsampleFN <- "data/newsample.csv"
newsample <- read(newsampleFN)
classify(newsample, classificationModel)

Validation

accuracy(validate(trainingset))

Datasets

With the package are provided also the following datasets from MIDClass []:

• Brain_Cancer.csv
• BRC_01.csv
• BRC_2.csv
• Gastric_Cancer.csv
• Lung_Cancer_1.csv
• Lung_Cancer_2.csv
• Lymphoma_Cancer.csv
• Melanoma_Cancer.csv
• Myeloma_Cancer.csv
• Pacreatic_Cancer.csv
• Prostate_Cancer.csv

the paths to them can be retrieved with

system.file("extdata", "<dataset filename>", package="uarray")

References

Rosalba Giugno, Alfredo Pulvirenti, Luciano Cascione, Giuseppe Pigola, Alfredo Ferro.
MIDClass: Microarray Data Classification by Association Rules and Gene Expression Intervals.
MIDClass []

Smyth, G. K.
Linear models and empirical Bayes methods for assessing differentiale expression in microarray experiments.
Statistical Applications in Genetics and Molecular Biology, (2004), Vol. 3, No. 1, Article 3.
Limma []

J. Alcalá-Fdez, L. Sánchez, S. García, M.J. del Jesus, S. Ventura, J.M. Garrell, J. Otero, C. Romero, J. Bacardit, V.M. Rivas, J.C. Fernández, F. Herrera.
KEEL: A Software Tool to Assess Evolutionary Algorithms to Data Mining Problems.
Soft Computing 13:3 (2009) 307-318, doi: 10.1007/s00500-008-0323-y.

J. Alcalá-Fdez, A. Fernandez, J. Luengo, J. Derrac, S. García, L. Sánchez, F. Herrera.
KEEL Data-Mining Software Tool: Data Set Repository, Integration of Algorithms and Experimental Analysis Framework.
Journal of Multiple-Valued Logic and Soft Computing 17:2-3 (2011) 255-287.

Michael Hahsler, Christian Buchta, Bettina Grün and Kurt Hornik.
Introduction to arules – A computational environment for mining association rules and frequent item sets