Introduce dataframe method for weave functions

DESCRIPTION

@@ -1,5 +1,5 @@
 Package: ariadne
-Version: 0.2.6
+Version: 0.2.7
 Authors@R: 
     c(person(given = "Giulio", family = "Benedetti", role = c("aut", "cre"),
           email = "giulio.benedetti@utu.fi",
@@ -37,7 +37,7 @@ Imports:
     ggplot2,
     ggraph,
     httr2,
-    igraph,
+    igraph (>= 2.3.0),
     KEGGREST,
     Matrix,
     methods,

NEWS

@@ -1,6 +1,6 @@
 Changes in version 0.2.x
 * Made major changes to workflow
-* Switched to S4 
+* Switched back to S4
 
 Changes in version 0.1.X
 * Switched to S7

R/data.R

@@ -26,3 +26,29 @@
 #' @name butyrate
 #' @importFrom utils data
 NULL
+
+
+#' Data frame for pathway from chebi to gmm
+#' 
+#' \code{pathMeta} provides a minimal example of a data frame describing one
+#' pathway in the ariadne graph from chebi to gmm. This kind of data frame is
+#' typically the output of \code{\link{drawPath}} and works as input for
+#' \code{\link{weavePath}} and \code{\link{weaveComplex}}.
+#' 
+#' @returns
+#' A pathway data frame with four rows (steps) and four columns (from, to,
+#' source and version).
+#' 
+#' @examples
+#' # Import data frame for pathway from chebi to gmm
+#' data("pathMeta", package = "ariadne")
+#' 
+#' # Print pathway data frame
+#' pathMeta
+#' 
+#' # Recreate pathMeta using ariadne
+#' # graph <- ariadne()
+#' # pathMeta <- drawPath(graph, chebi ~ gmm, include = "rhea")
+#' @name pathMeta
+#' @importFrom utils data
+NULL

R/draw.R

@@ -106,7 +106,7 @@ setMethod("drawPath", signature = c(graph = "igraph"),
     # Create path data.frame
     path_df <- data.frame(
         from = nodes[-length(nodes)],
-        to = nodes[-1],
+        to = nodes[-1L],
         source = edges
     )
     return(path_df)

R/plot.R

@@ -57,10 +57,10 @@ setMethod("plotPath", signature = c(graph = "igraph"),
     function(graph, by = NULL, k = 1, include = NULL, exclude = NULL,
     res.name = NULL, prune = FALSE, focus = FALSE){
     # Check args
-    if( !is.logical(prune) || length(prune) != 1L ){
+    if( length(prune) != 1L || !is.logical(prune) || is.na(prune) ){
         stop("'prune' must be TRUE or FALSE.", call. = FALSE)
     }
-    if( !is.logical(focus) || length(focus) != 1L ){
+    if( length(focus) != 1L || !is.logical(focus) || is.na(focus) ){
         stop("'focus' must be TRUE or FALSE.", call. = FALSE)
     }
 

R/utils.R

@@ -26,6 +26,9 @@ NULL
 #' @export
 #' @rdname listResourceVersions
 listResourceVersions <- function(default = FALSE){
+    if( length(default) != 1L || !is.logical(default) || is.na(default) ){
+        stop("'default' must be TRUE or FALSE.", call. = FALSE)
+    }
     # Retrieve metadata on resource versions
     meta <- versionMetadata
     # If default is turned on

R/weave.R

@@ -13,7 +13,8 @@
 #' coverage threshold, which is useful for pathways or functional modules made
 #' of several indispensable components.
 #' 
-#' @param graph An igraph object.
+#' @param graph An igraph or data.frame object, which can be obtained from
+#'   \code{\link{ariadne}} and \code{\link{drawPath}}, respectively.
 #' 
 #' @param by A formula specifying the path to weave.
 #' 
@@ -65,15 +66,33 @@
 #' column.
 #' 
 #' @examples
+#' # Load resource graph
+#' graph <- ariadne()
+#' 
+#' # Weave simple path from KEGG diseases to gut metabolic modules
+#' dis2gmm <- weavePath(graph, kegg_disease ~ gmm)
+#' 
+#' # Weave complex path from KEGG diseases to gut metabolic modules
+#' dis2gmm <- weaveComplex(graph, kegg_disease ~ gmm)
+#' 
+#' # Specify coverage threshold
+#' dis2gmm <- weaveComplex(graph, kegg_disease ~ gmm, threshold = 0.8)
+#' 
+#' 
+#' # Load example pathway dataframe
+#' data("pathMeta", package = "ariadne")
+#' 
+#' # Weave pathway from chebi to gmm with three initial chebi ids
+#' chebi2gmm <- weavePath(pathMeta, init = c(15377, 30616, 4167))
+#' 
+#' 
+#' # Import mia package
 #' library(mia)
 #' 
 #' # Import dataset
 #' data("Tengeler2020", package = "mia")
 #' tse <- Tengeler2020
 #' 
-#' # Load resource graph
-#' graph <- ariadne()
-#' 
 #' # Retrieve taxon names
 #' tax.labs <- getTaxonomyLabels(tse, make.unique = FALSE)
 #' tax.labs <- sub("^.+:", "", tax.labs)
@@ -88,18 +107,59 @@
 #' tax2bugsig <- weavePath(
 #'     graph, taxname ~ bugsig, include = "taxid", init = tax.labs
 #' )
-#' 
-#' # Weave simple path from KEGG diseases to gut metabolic modules
-#' dis2gmm <- weavePath(graph, kegg_disease ~ gmm)
-#' 
-#' # Weave complex path from KEGG diseases to gut metabolic modules
-#' dis2gmm <- weaveComplex(graph, kegg_disease ~ gmm)
-#' 
-#' # Specify coverage threshold
-#' dis2gmm <- weaveComplex(graph, kegg_disease ~ gmm, threshold = 0.8)
 NULL
 
 
+#' @export
+#' @rdname weavePath
+#' @importFrom stats as.formula
+setMethod("weavePath", signature = c(graph = "data.frame"),
+    function(graph, init = NULL, prune = TRUE, use.names = TRUE, verbose = TRUE,
+    timeout = 1e6, ...){
+    # Derive formula from pathway dataframe
+    by <- c(graph$from[1L], graph$to[nrow(graph)]) |>
+        paste(collapse = "~") |>
+        as.formula()
+    # Retrieve minimal graph for the pathway
+    graph <- .graph_from_path_df(graph)
+    # Weave linkmap from minimal graph
+    linkmap <- weavePath(
+        graph, by, init = init, prune = prune, use.names = use.names,
+        verbose = verbose, timeout = timeout, ...
+    )
+    return(linkmap)
+})
+
+
+#' @importFrom igraph as_data_frame subgraph_from_edges
+.graph_from_path_df <- function(path_df){
+    # If versions are provided
+    if( "version" %in% names(path_df) ){
+        # Derive versions from pathway dataframe
+        res_df <- unique(path_df[ , c("source", "version")])
+        # Omit missing versions
+        res_df <- na.omit(res_df)
+        # Create versions list
+        versions <- as.list(res_df$version)
+        names(versions) <- res_df$source
+    }else{
+        # Use empty versions
+        versions <- NULL
+    }
+    # Import ariadne graph
+    graph <- ariadne(versions = versions)
+    # Get keys of graph edges
+    E(graph)$name <- graph |>
+        as_data_frame(what = "edges") |>
+        .get_edge_keys()
+    # Get keys of pathway steps
+    keep <- .get_edge_keys(path_df)
+    # Subset graph based on pathway steps
+    graph <- subgraph_from_edges(graph, keep)
+    return(graph)
+}
+
+
 #' @export
 #' @rdname weavePath
 #' @importFrom stats as.formula
@@ -132,10 +192,10 @@ setMethod("weavePath", signature = c(graph = "igraph"),
         stop("'timeout' must be a positive number", call. = FALSE)
     }
     # Check shared logical args
-    if( !is.logical(prune) || length(prune) != 1L ){
+    if( length(prune) != 1L || !is.logical(prune) || is.na(prune) ){
         stop("'prune' must be TRUE or FALSE.", call. = FALSE)
     }
-    if( !is.logical(verbose) || length(verbose) != 1L ){
+    if( length(verbose) != 1L || !is.logical(verbose) || is.na(verbose) ){
         stop("'verbose' must be TRUE or FALSE.", call. = FALSE)
     }
     # Set timeout for downloads

R/weave_complex.R

@@ -1,4 +1,25 @@
 
+#' @export
+#' @rdname weavePath
+#' @importFrom stats as.formula
+setMethod("weaveComplex", signature = c(graph = "data.frame"),
+    function(graph, init = NULL, prune = TRUE, use.names = TRUE,
+    threshold = NULL, verbose = TRUE, timeout = 1e6, ...){
+
+    by <- c(graph$from[1L], graph$to[nrow(graph)]) |>
+        paste(collapse = "~") |>
+        as.formula()
+
+    graph <- .graph_from_path_df(graph)
+
+    linkmap <- weaveComplex(
+        graph, by, init = init, prune = prune, use.names = use.names,
+        threshold = threshold, verbose = verbose, timeout = timeout, ...
+    )
+    return(linkmap)
+})
+
+
 #' @export
 #' @rdname weavePath
 #' @importFrom igraph as_data_frame
@@ -36,7 +57,6 @@ setMethod("weaveComplex", signature = c(graph = "igraph"),
     }else{
         inner_by <- by
     }
-
     # Build MultiFactor from path linkmaps
     mf <- .build_path_mf(
         graph, inner_by, k, include, exclude, res.name,