AdjacencyMatrix | R Documentation |

The function 'AdjacencyMatrix' will create an object of type 'AdjacencyMatrix'.

AdjacencyMatrix( adj_l, rowData, type = c("structural", "statistical", "combine"), directed = c(TRUE, FALSE), thresholded = c(TRUE, FALSE) )

`adj_l` |
'list' of adjacency matrices |

`rowData` |
'data.frame', containing information on the features |

`type` |
'character', either '"structural"', '"statistical"', or '"combine"' |

`directed` |
'logical', if the adjacency matrix underlying the graph is directed or undirected |

`thresholded` |
'logical', if the functions 'rtCorrection' or 'threshold' were applied on the 'structural' or 'statistical' 'AdjacencyMatrix' objects |

'adj_l' is a list of adjacency matrices. The adjacency matrices have identical dimensions and 'dimnames' and each adjacency matrix has the same number of columns and rows and identical 'rownames' and 'colnames'. 'rowData' will be also used for the 'colData' slot (since the 'rownames' and 'colnames' are identical).

object of S4 class 'AdjacencyMatrix'

- The 'AdjacencyMatrix' class extends the [SummarizedExperiment::SummarizedExperiment] class and inherits all its accessors and replacement methods.

- The 'type' accessor returns the 'type' ('"structural"', '"statistical"', '"combine"') slot.

- The 'directed' accessor returns the 'directed' ('logical' of length 1) slot.

- The 'thresholded' accessor returns the 'thresholded' ('logical' of length 1) slot.

Thomas Naake, thomasnaake@googlemail.com

binary <- matrix(0, ncol = 10, nrow = 10) transformation <- matrix("", ncol = 10, nrow = 10) mass_difference <- matrix("", ncol = 10, nrow = 10) rownames(binary) <- rownames(transformation) <- rownames(mass_difference) <- paste("feature", 1:10) colnames(binary) <- rownames(transformation) <- rownames(mass_difference) <- paste("feature", 1:10) binary[5, 4] <- 1 transformation[5, 4] <- "glucose addition" mass_difference[5, 4] <- "162" ## create adj_l and rowData adj_l <- list(binary = binary, transformation = transformation, mass_difference = mass_difference) rowData <- DataFrame(features = rownames(binary), row.names = rownames(binary)) AdjacencyMatrix(adj_l = adj_l, rowData = rowData, type = "structural", directed = TRUE, thresholded = FALSE)

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