Machine Learning Interface for RNA-Seq Data


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Documentation for package ‘MLSeq’ version 2.23.0

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MLSeq-package Machine learning interface for RNA-Seq data
Available-classifiers Available classification/regression methods in 'MLSeq'
availableMethods Available classification/regression methods in 'MLSeq'
cervical Cervical cancer data
classify Fitting classification models to sequencing data
confusionMat Accessors for the 'confusionMat' slot.
confusionMat-method Accessors for the 'confusionMat' slot.
control Accessors for the 'control' slot.
control-method Accessors for the 'control' slot.
control<- Accessors for the 'control' slot.
control<--method Accessors for the 'control' slot.
discrete.train-class 'discrete.train' object
discreteControl Define controlling parameters for discrete classifiers (NBLDA and PLDA)
input Accessors for the 'inputObject' slot of an 'MLSeq' object
input-method Accessors for the 'inputObject' slot of an 'MLSeq' object
isModified Checks if MLSeq object is updated/modified or not.
isModified-method Checks if MLSeq object is updated/modified or not.
isModified<- Checks if MLSeq object is updated/modified or not.
isModified<--method Checks if MLSeq object is updated/modified or not.
isUpdated Checks if MLSeq object is updated/modified or not.
isUpdated-method Checks if MLSeq object is updated/modified or not.
isUpdated<- Checks if MLSeq object is updated/modified or not.
isUpdated<--method Checks if MLSeq object is updated/modified or not.
metaData Accessors for the 'metaData' slot of an 'MLSeq' object
metaData-method Accessors for the 'metaData' slot of an 'MLSeq' object
method Accessors for the 'method'.
method-method Accessors for the 'method'.
method<- Accessors for the 'method'.
method<--method Accessors for the 'method'.
MLSeq-class 'MLSeq' object
MLSeqMetaData-class 'MLSeqMetaData' object
MLSeqModelInfo-class 'MLSeqModelInfo' object
modelInfo Accessors for the 'modelInfo' slot of an 'MLSeq' object
modelInfo-method Accessors for the 'modelInfo' slot of an 'MLSeq' object
normalization Accessors for the 'normalization' slot.
normalization-method Accessors for the 'normalization' slot.
normalization<- Accessors for the 'normalization' slot.
normalization<--method Accessors for the 'normalization' slot.
plot Plot accuracy results from 'MLSeq' object
plot-method Plot accuracy results from 'MLSeq' object
plot.MLSeq Plot accuracy results from 'MLSeq' object
predict Extract predictions from 'classify()' object
predict-method Extract predictions from 'classify()' object
predict.MLSeq Extract predictions from 'classify()' object
predictClassify Extract predictions from 'classify()' object
preProcessing Accessors for the 'preProcessing' slot of an 'MLSeq' object
preProcessing-method Accessors for the 'preProcessing' slot of an 'MLSeq' object
preProcessing<- Accessors for the 'preProcessing' slot of an 'MLSeq' object
preProcessing<--method Accessors for the 'preProcessing' slot of an 'MLSeq' object
print-method Print method for confusion matrix
print.confMat Print method for confusion matrix
printAvailableMethods Available classification/regression methods in 'MLSeq'
ref Accessors for the 'ref' slot.
ref-method Accessors for the 'ref' slot.
ref<- Accessors for the 'ref' slot.
ref<--method Accessors for the 'ref' slot.
selectedGenes Accessors for the 'selectedGenes'.
selectedGenes-method Accessors for the 'selectedGenes'.
show Show method for MLSeq objects
show-method Show method for MLSeq objects
show.MLSeq Show method for MLSeq objects
trained Accessors for the 'trainedModel' slot.
trained-method Accessors for the 'trainedModel' slot.
trainParameters Accessors for the 'trainParameters' slot.
trainParameters-method Accessors for the 'trainParameters' slot.
transformation Accessors for the 'transformation' slot.
transformation-method Accessors for the 'transformation' slot.
update Update 'MLSeq' objects returnd from 'classify()'
update-method Update 'MLSeq' objects returnd from 'classify()'
update.MLSeq Update 'MLSeq' objects returnd from 'classify()'
voom.train-class 'voom.train' object
voomControl Define controlling parameters for voom-based classifiers