Description Usage Arguments See Also Examples
This slot stores the name of selected genes which are used in the classifier.
The trained model is stored in slot trainedModel. See trained for details.
1 2 3 4 | selectedGenes(object)
## S4 method for signature 'MLSeq'
selectedGenes(object)
|
object |
an |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 | ## Not run:
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 (30% test, 70% train).
nTest <- ceiling(n*0.3)
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(~ 1))
## Number of repeats (repeats) might change model accuracies ##
# Classification and Regression Tree (CART) Classification
cart <- classify(data = data.trainS4, method = "rpart",
ref = "T", preProcessing = "deseq-vst",
control = trainControl(method = "repeatedcv", number = 5,
repeats = 3, classProbs = TRUE))
selectedGenes(cart)
## End(Not run)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.