saga_sampling will prepare training and testing data of the joint SAGA data set. An internal process is used to filter all data for candidate probes suited for classification of array data into transforming/untransforming. The list cannot be changed in this version and the package is optimized for this specific gene set. Also, a PCA plot may be generated to monitor the generalized context of the sample data within the SAGA training set.

saga_sampling(matrix.SAGA, matrix.test)

Arguments

matrix.SAGA

Matrix with SAGA model data

matrix.test

Matrix with user sample or test data

Value

matrix.train normalized, probe-averaged and batch-corrected SAGA training data.

labels.train class labels (factors) for SAGA training data. Can either be "transforming" or "untransforming".

matrix.unknown matrix of sample data with array names as row names and probes as column names.