transformation: Accessors for the 'transformation' slot of an 'MLSeq' object

Description Usage Arguments Author(s) Examples

Description

This slot stores the name of transformation method which is used while transforming the count data (i.e. either "vst" or "voomCPM")

Usage

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transformation(object)

## S4 method for signature 'MLSeq'
transformation(object)

Arguments

object

an MLSeq object.

Author(s)

Gokmen Zararsiz

Examples

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library(DESeq2)
data(cervical)

# a subset of cervical data with first 150 features.
data <- cervical[c(1:150),]

# defining sample classes.
class <- data.frame(condition=factor(rep(c("N","T"), c(29,29))))

n <- ncol(data)  # number of samples
p <- nrow(data)  # number of features

# number of samples for test set (20% test, 80% train).
nTest <- ceiling(n*0.2)
ind <- sample(n, nTest, FALSE)

# train set
data.train <- data[,-ind]
data.train <- as.matrix(data.train + 1)
classtr <- data.frame(condition=class[-ind, ])

# train set in S4 class
data.trainS4 <- DESeqDataSetFromMatrix(countData = data.train,
                  colData = classtr, formula(~ condition))
data.trainS4 <- DESeq(data.trainS4, fitType = "local")

# Classification and Regression Trees (CART)
cart <- classify(data = data.trainS4, method = "cart",
          transformation = "vst", ref = "T", normalize = "deseq",
          control = trainControl(method = "repeatedcv", number = 5,
                                 repeats = 3, classProbs = TRUE))

transformation(cart)

gokmenzararsiz/MLSeq documentation built on May 17, 2019, 7:41 a.m.