genModelList {MultiBaC} | R Documentation |
This function performs PLS models for every batch. A PLS model is generated for each non-common omic in each batch.
genModelList(mbac, test.comp = NULL, scale = FALSE, center = TRUE, crossval = NULL, showinfo = TRUE)
mbac |
mbac object generated by *createMbac*. |
test.comp |
Maximum number of components allowed for PLS models. If NULL (default), the minimal effective rank of the matrices is used as the maximum number of components. |
scale |
Logical. Whether X and Y matrices must be scaled. By default, FALSE. |
center |
Logical. Whether X and Y matrices must be centered. By default, TRUE. |
crossval |
Integer: number of cross-validation segments. The number of samples (rows of 'x') must be at least >= crossvalI. If NULL (default) leave-one-out crossvalidation is performed. |
showinfo |
Logical. Whether to show the information about the function progress. By default, TRUE. |
Custom mbac object. Elements in a mbac object:
ListOfBatches: A list of MultiAssayExperiment objects (one per batch).
commonOmic: Name of the common omic between the batches.
PLSmodels: PLS models created during MultiBaC method performance (one model per non-common omic data type).
InnerRelation: Table of class data.frame containing the inner correlation (i.e. correlation between the scores of X (t) and Y (u) matrices) for each PLS model across all components.
data('multiyeast') my_mbac <- createMbac (inputOmics = list(A.rna, A.gro, B.rna, B.ribo, C.rna, C.par), batchFactor = c("A", "A", "B", "B", "C", "C"), experimentalDesign = list("A" = c("Glu+", "Glu+", "Glu+", "Glu-", "Glu-", "Glu-"), "B" = c("Glu+", "Glu+", "Glu-", "Glu-"), "C" = c("Glu+", "Glu+", "Glu-", "Glu-")), omicNames = c("RNA", "GRO", "RNA", "RIBO", "RNA", "PAR"), commonOmic = "RNA") my_mbac_2 <- genModelList (my_mbac, test.comp = NULL, scale = FALSE, center = TRUE, crossval = NULL, showinfo = TRUE)