R: An Interface for PoiClaClu Package's Classify Function

classifyInterface {ClassifyR}

R Documentation

An Interface for PoiClaClu Package's Classify Function

Description

More details of Poisson LDA are available in the documentation of Classify.

Usage

  ## S4 method for signature 'matrix'
classifyInterface(measurements, classes, test, ...)
  ## S4 method for signature 'DataFrame'
classifyInterface(measurements, classes, test, ..., verbose = 3)
  ## S4 method for signature 'MultiAssayExperiment'
classifyInterface(measurements, test, targets = names(measurements), ...)

Arguments

`measurements`	Either a `matrix`, `DataFrame` or `MultiAssayExperiment` containing the training data. For a `matrix`, the rows are features, and the columns are samples. If of type `DataFrame`, the data set is subset to only those features of type `integer`.
`classes`	Either a vector of class labels of class `factor` of the same length as the number of samples in `measurements` or if the measurements are of class `DataFrame` a character vector of length 1 containing the column name in `measurement` is also permitted. Not used if `measurements` is a `MultiAssayExperiment` object.
`test`	An object of the same class as `measurements` with no samples in common with `measurements` and the same number of features as it.
`targets`	If `measurements` is a `MultiAssayExperiment`, the names of the data tables to be used. `"clinical"` is also a valid value and specifies that integer variables from the clinical data table will be used.
`...`	Variables not used by the `matrix` nor the `MultiAssayExperiment` method which are passed into and used by the `DataFrame` method or parameters that `Classify` can accept.
`verbose`	Default: 3. A number between 0 and 3 for the amount of progress messages to give. This function only prints progress messages if the value is 3.

Details

Data tables which consist entirely of non-integer data cannot be analysed. If measurements is an object of class MultiAssayExperiment, the factor of sample classes must be stored in the DataFrame accessible by the colData function with column name "class".

Value

A result list, the same as is returned by Classify.

Author(s)

Dario Strbenac

Examples

  if(require(PoiClaClu))
  {
    readCounts <- CountDataSet(n = 100, p = 1000, 2, 5, 0.1)
    # Rows are for features, columns are for samples.
    trainData <- t(readCounts[['x']])
    classes <- readCounts[['y']]
    testData <- t(readCounts[['xte']])
    storage.mode(trainData) <- storage.mode(testData) <- "integer"
    classified <- classifyInterface(trainData, classes, testData)
    
    setNames(table(readCounts[["yte"]] == classified[["ytehat"]]),
             c("Incorrect", "Correct"))
  }

[Package ClassifyR version 2.0.10 Index]