Merge pull request #58 from federicomarini/new_igraph

New igraph changes - brought in for GeneTonic

DESCRIPTION

@@ -1,8 +1,8 @@
 Package: GeneTonic
 Title: Enjoy Analyzing And Integrating The Results From Differential Expression 
     Analysis And Functional Enrichment Analysis
-Version: 2.7.1
-Date: 2024-01-10
+Version: 2.7.2
+Date: 2024-02-16
 Authors@R: 
     c(
         person(
@@ -84,7 +84,7 @@ Encoding: UTF-8
 VignetteBuilder: knitr
 URL: https://github.com/federicomarini/GeneTonic
 BugReports: https://github.com/federicomarini/GeneTonic/issues
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.1
 Roxygen: list(markdown = TRUE)
 biocViews:
     GUI, GeneExpression, Software, Transcription, Transcriptomics, Visualization,

NAMESPACE

@@ -140,14 +140,14 @@ importFrom(igraph,V)
 importFrom(igraph,add_edges)
 importFrom(igraph,as_adjacency_matrix)
 importFrom(igraph,as_biadjacency_matrix)
+importFrom(igraph,as_edgelist)
 importFrom(igraph,degree)
-importFrom(igraph,delete.edges)
+importFrom(igraph,delete_edges)
 importFrom(igraph,delete_vertices)
-importFrom(igraph,get.edgelist)
-importFrom(igraph,graph.data.frame)
+importFrom(igraph,graph_from_data_frame)
 importFrom(igraph,induced_subgraph)
 importFrom(igraph,make_full_graph)
-importFrom(igraph,permute.vertices)
+importFrom(igraph,permute)
 importFrom(igraph,strength)
 importFrom(igraph,vcount)
 importFrom(matrixStats,rowSds)

NEWS.md

@@ -3,6 +3,8 @@
 ## Other notes
 
 * Updated functions used from other packages to reflect changes in their API/nomenclature
+* Adapted the internal code of functions to the latest version of `igraph` - no changes happening 
+for the end user
 
 # GeneTonic 2.6.0
 

R/GeneTonic-extras.R

@@ -683,7 +683,7 @@ export_to_sif <- function(g, sif_file = "", edge_label = "relates_to") {
   sif_file <- normalizePath(sif_file, mustWork = FALSE)
   stopifnot(is.character(edge_label) && length(edge_label) == 1)
 
-  el <- get.edgelist(g)
+  el <- as_edgelist(g)
   sif_df <- data.frame(
     n1 = el[, 1],
     edge_label = edge_label,

R/GeneTonic-pkg.R

@@ -12,8 +12,6 @@
 #' the live session, and creating an HTML report as an artifact where text,
 #' code, and output coexist.
 #'
-#' @author Federico Marini \email{marinif@@uni-mainz.de}
-#'
 #' @importFrom AnnotationDbi Definition GOID Ontology Secondary Synonym Term
 #' @importFrom backbone backbone.extract fdsm fixedrow sdsm
 #' @importFrom bs4Dash bs4Card bs4DashBody bs4DashControlbar
@@ -43,8 +41,8 @@
 #' @importFrom grDevices colorRampPalette rgb col2rgb
 #' @importFrom grid gpar
 #' @importFrom igraph add_edges as_adjacency_matrix as_biadjacency_matrix degree
-#' delete.edges delete_vertices "%du%" E "E<-" graph.data.frame induced_subgraph
-#' make_full_graph permute.vertices strength V "V<-" vcount get.edgelist
+#' delete_edges delete_vertices "%du%" E "E<-" graph_from_data_frame induced_subgraph
+#' make_full_graph permute strength V "V<-" vcount as_edgelist
 #' @importFrom matrixStats rowSds
 #' @importFrom methods is
 #' @importFrom plotly ggplotly plotlyOutput renderPlotly plot_ly layout add_trace
@@ -71,5 +69,5 @@
 #' @importFrom viridis viridis
 #'
 #' @name GeneTonic-pkg
-#' @docType package
-NULL
+#' @keywords internal
+"_PACKAGE"

R/GeneTonic.R

@@ -930,7 +930,7 @@ GeneTonic <- function(dds = NULL,
       # rank_gs <- rank(V(g)$name[V(g)$nodetype == "GeneSet"])
       # rank_feats <- rank(V(g)$name[V(g)$nodetype == "Feature"]) +
       #   length(rank_gs) # to keep the GeneSets first
-      # g <- permute.vertices(g, c(rank_gs, rank_feats))
+      # g <- permute(g, c(rank_gs, rank_feats))
       # return(g)
     })
 
@@ -1288,7 +1288,7 @@ GeneTonic <- function(dds = NULL,
         color_by = input$emap_colorby
       )
       # rank_gs <- rank(V(emg)$name)
-      # emg <- permute.vertices(emg, rank_gs)
+      # emg <- permute(emg, rank_gs)
       return(emg)
     })
 

R/enrichment_map.R

@@ -144,10 +144,10 @@ enrichment_map <- function(res_enrich,
   # omm <- omm[!is.na(omm$value), ]
 
   # use this to construct the graph
-  emg <- graph.data.frame(omm[, c(1, 2)], directed = FALSE)
+  emg <- graph_from_data_frame(omm[, c(1, 2)], directed = FALSE)
 
   E(emg)$width <- sqrt(omm$value * scale_edges_width)
-  emg <- delete.edges(emg, E(emg)[omm$value < overlap_threshold])
+  emg <- delete_edges(emg, E(emg)[omm$value < overlap_threshold])
 
   idx <- match(V(emg)$name, res_enrich$gs_description)
 
@@ -237,7 +237,7 @@ enrichment_map <- function(res_enrich,
 
   # re-sorting the vertices alphabetically
   rank_gs <- rank(V(emg)$name)
-  emg <- permute.vertices(emg, rank_gs)
+  emg <- permute(emg, rank_gs)
 
   return(emg)
 }

R/ggs_graph.R

@@ -157,7 +157,7 @@ ggs_graph <- function(res_enrich,
   })
   list2df <- do.call("rbind", list2df)
 
-  g <- graph.data.frame(list2df, directed = FALSE)
+  g <- graph_from_data_frame(list2df, directed = FALSE)
 
   nodeIDs_gs <- which(names(V(g)) %in% enriched_gsnames)
   nodeIDs_genes <- which(!(names(V(g)) %in% enriched_gsnames))
@@ -212,7 +212,7 @@ ggs_graph <- function(res_enrich,
   rank_gs <- rank(V(g)$name[V(g)$nodetype == "GeneSet"])
   rank_feats <- rank(V(g)$name[V(g)$nodetype == "Feature"]) +
     length(rank_gs) # to keep the GeneSets first
-  g <- permute.vertices(g, c(rank_gs, rank_feats))
+  g <- permute(g, c(rank_gs, rank_feats))
 
   return(g)
 }

tests/testthat/test-gs_dendro.R

@@ -30,7 +30,7 @@ test_that("Gene set dendrogram is created", {
   expect_is(my_dend_pval, "dendrogram")
 
   re_subset <- res_enrich_withscores[res_enrich_withscores[1:12, ]$z_score >= 0, ]
-  my_dend_subset <- gs_dendro(re_subset, n_gs = 12, color_leaves_by = "z_score")
+  my_dend_subset <- gs_dendro(re_subset, n_gs = 18, color_leaves_by = "z_score")
   expect_is(my_dend_subset, "dendrogram")
 
   expect_warning(gs_dendro(res_enrich_withscores,