Description Usage Arguments Value Examples
This function performs PLS models for every batch. A PLS model is generated for each non-common omic in each batch.
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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.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | 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)
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