confusionMat: Accessors for the 'confusionMat' slot of an 'MLSeq' object
In gokmenzararsiz/MLSeq: Machine Learning Interface for RNA-Seq Data

Description Usage Arguments Details Author(s) See Also Examples

This slot stores the confusion matrix for the trained model using classify function.

confusionMat(object)

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

object

an MLSeq object.

confusionMat slot includes information about cross-tabulation of observed and predicted classes and corresponding statistics such as accuracy rate, sensitivity, specifity, etc. The returned object is in confusionMatrix class of caret package. See confusionMatrix for details.

Gokmen Zararsiz

confusionMatrix

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))

confusionMat(cart)