1. KEGGlincs
  2. Commit 4614338ba87ceeb7e4fe74c4e785d0b9770ca951
Browse code

Adding KEGGlincs, flowPloidy, MAST, PathoStat, matter, MoonlightR, psichomics, anamiR, MutationalPatterns, HelloRanges, crisprseekplus, annotatr, meshes

git-svn-id: file:///home/git/hedgehog.fhcrc.org/bioconductor/trunk/madman/Rpacks/KEGGlincs@122278 bc3139a8-67e5-0310-9ffc-ced21a209358

Martin Morgan authored on 12/10/2016 17:44:52
Showing 57 changed files
.Rbuildignore
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+^.*\.Rproj$
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+^\.Rproj\.user$
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+^README\.md$
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+^image_files$
.gitignore
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+.Rproj.user
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+.Rhistory
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+.RData
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+.Ruserdata
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+inst/doc
DESCRIPTION
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+Package: KEGGlincs
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+Type: Package
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+Title: Visualize all edges within a KEGG pathway and overlay LINCS data
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+        [option]
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+Version: 0.99.4
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+Date: 2016-06-02
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+Author: Shana White
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+Maintainer: Shana White <vandersm@mail.uc.edu>
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+Description: See what is going on 'under the hood' of KEGG pathways by
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+        explicitly re-creating the pathway maps from information
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+        obtained from KGML files.
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+License: GPL-3
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+LazyData: true
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+RoxygenNote: 5.0.1
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+Depends: R (>= 3.3), KOdata, hgu133a.db, org.Hs.eg.db (>= 3.3.0)
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+SystemRequirements: Cytoscape (>= 3.3.0), Java (>= 8)
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+Suggests: BiocInstaller (>= 1.20.3), knitr, rmarkdown, graph
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+biocViews: NetworkInference, GeneExpression, DataRepresentation,
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+        ThirdPartyClient,CellBiology,GraphAndNetwork,Pathways,KEGG,Network
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+Imports:
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+        AnnotationDbi,KEGGgraph,igraph,plyr,gtools,httr,RJSONIO,KEGGREST,
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+        methods,graphics,stats,utils
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+VignetteBuilder: knitr
KEGGlincs.Rproj
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+Version: 1.0
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+
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+RestoreWorkspace: Default
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+SaveWorkspace: Default
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+AlwaysSaveHistory: Default
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+
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+EnableCodeIndexing: Yes
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+UseSpacesForTab: Yes
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+NumSpacesForTab: 4
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+Encoding: UTF-8
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+
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+RnwWeave: Sweave
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+LaTeX: pdfLaTeX
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+
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+BuildType: Package
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+PackageUseDevtools: Yes
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+PackageInstallArgs: --no-multiarch --with-keep.source
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+PackageBuildArgs: --resave-data
NAMESPACE
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+# Generated by roxygen2: do not edit by hand
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+
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+export(KEGG_lincs)
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+export(add_edge_data)
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+export(cyto_vis)
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+export(edge_mapping_info)
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+export(expand_KEGG_edges)
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+export(expand_KEGG_mappings)
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+export(generate_mappings)
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+export(get_KGML)
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+export(get_fisher_info)
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+export(get_graph_object)
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+export(node_mapping_info)
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+export(overlap_info)
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+export(path_genes_by_cell_type)
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+export(refine_mappings)
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+export(toCytoscape)
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+import(AnnotationDbi)
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+import(KEGGREST)
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+import(KOdata)
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+import(RJSONIO)
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+import(hgu133a.db)
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+import(httr)
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+import(methods)
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+import(org.Hs.eg.db)
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+importFrom(graphics,barplot)
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+importFrom(graphics,legend)
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+importFrom(graphics,par)
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+importFrom(gtools,smartbind)
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+importFrom(igraph,"V<-")
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+importFrom(igraph,E)
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+importFrom(igraph,V)
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+importFrom(igraph,ecount)
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+importFrom(igraph,edge.attributes)
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+importFrom(igraph,edge_attr)
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+importFrom(igraph,get.edgelist)
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+importFrom(igraph,graph.attributes)
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+importFrom(igraph,list.edge.attributes)
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+importFrom(igraph,list.vertex.attributes)
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+importFrom(igraph,vertex.attributes)
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+importFrom(plyr,rename)
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+importFrom(stats,fisher.test)
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+importFrom(stats,p.adjust)
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+importFrom(stats,p.adjust.methods)
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+importFrom(utils,combn)
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+importFrom(utils,data)
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+importMethodsFrom(KEGGgraph,edges)
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+importMethodsFrom(KEGGgraph,nodes)
NEWS
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+News for KEGGlincs
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\ No newline at end of file
R/KEGG_lincs.R
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+#' Combines all other package functions for one-step pathway visualization
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+#' @export
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+#' @param pathwayid A KEGG pathway ID of the form "hsa12345"
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+#' (only human pathways currently)
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+#' @param cell_line If left as NA will generate a pathway map without
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+#' data-dependent attributes (such as edge width).  To use in combination
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+#' with LINCS data, choose from the set of cell lines:
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+#' (A375,A549,ASC,HA1E,HCC515,HEK293T,HEKTE,HEPG2,HT29,MCF7,NCIH716,NPC,PC3,
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+#' SHSY5Y,SKL,SW480,VCAP)
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+#' @param refine_by_cell_line A logical indicator
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+#' @param add_L1000_edge_data A logical indicator
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+#' @param data_type Choose from data types: (100_full, 100_bing, 50_lm)
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+#' @param pert_time Choose from (6,24,48,96,120,144,168)
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+#' @param only_mapped A logical indicator; if set to FALSE will return 'de-novo'
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+#' edges that 'exist' in data but are not documented in KEGG
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+#' @param significance_markup A logical indicator; if set to TRUE will color
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+#'  edges based on direction and significance of correlation (as determined by
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+#'  user-data-analysis)
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+#' @param layered_nodes A logical indicator; if set to TRUE will create a graph
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+#' with 'stacked' nodes that the user can manipulate when multiple nodes are
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+#' mapped to one location
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+#' @param graph_title An optional user-specified graph title
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+#' @param get_data A logical indicator; if set to true, will return the
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+#' 'expanded' edge information for the specified pathway
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+#' @param convert_KEGG_IDs A logical indicator; if set to TRUE KEGG
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+#' compounds will remain labeled via KEGG codes (do not need KEGGREST)
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+#' @return  A dynamic map in Cytoscape automatically formatted for convenient
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+#' viewing and, if idicated by user, a data.frame object with detailed
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+#' information for 'expanded' KEGG edges
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+#' @examples \dontrun{
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+#'
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+#' #Default KEGG pathway with colored edges representing type of relationship:
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+#' KEGG_lincs("hsa04115", convert_KEGG_IDs = FALSE)
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+#'
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+#' #KEGG pathway with edge width and color based on observed experimental data:
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+#' KEGG_lincs("hsa04115", "HA1E")
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+#'
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+#' #Have edge information data.frame to be output to the global environment:
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+#' p53_edge_info <- KEGG_lincs("hsa04115", graph_title = "p53"
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+#'                              convert_KEGG_IDs = FALSE, get_data = TRUE)
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+#'                              }
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+
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+
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+KEGG_lincs <-
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+function(pathwayid, cell_line = NA,
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+                            refine_by_cell_line = NA,
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+                            add_L1000_edge_data = TRUE,
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+                            significance_markup = TRUE,
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+                            data_type = "100_full",
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+                            pert_time = 96,
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+                            only_mapped = TRUE,
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+                            layered_nodes = FALSE, graph_title = "default",
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+                            get_data = FALSE,
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+                            convert_KEGG_IDs = TRUE){
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+    if (is.na(refine_by_cell_line)){
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+        if (is.na(cell_line)){
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+            refine_by_cell_line <- FALSE
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+        }
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+        else {
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+            refine_by_cell_line <- TRUE
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+        }
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+    }
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+
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+    KGML <- get_KGML(pathwayid, get_if_no_edges = TRUE)
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+    if(!isS4(KGML)){
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+        return()
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+    }
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+    KEGG_mappings <-
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+        expand_KEGG_mappings(KGML,convert_KEGG_IDs = convert_KEGG_IDs)
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+    if (refine_by_cell_line) {
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+        full_mappings <- KEGG_mappings
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+        KEGG_mappings <- refine_mappings(KEGG_mappings, cell_line)
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+        for (i in 1:nrow(full_mappings)){
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+            if(!full_mappings$entryID[i] %in% KEGG_mappings$entryID){
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+                full_mappings$BGcolor[i] <- "#d3d3d3"
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+                full_mappings$in_relationship <- 0
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+            }
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+        }
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+    }
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+    expanded_edges <- expand_KEGG_edges(KGML, KEGG_mappings)
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+    if(expanded_edges$type[1] == "dummy"){
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+        graph_title <- paste0("Pathway = ", pathwayid, ":",
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+                        KGML@pathwayInfo@title, "Cell-Line: ", cell_line,
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+                        "  *No Edges in Pathway")
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+    }
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+
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+    if (is.na(cell_line)){
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+        edge_map <- edge_mapping_info(expanded_edges)
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+    if (graph_title == "default"){
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+        graph_title <- paste0("Pathway = ", pathwayid, ":",
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+                            KGML@pathwayInfo@title)
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+        }
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+    }
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+    if (!is.na(cell_line) & !add_L1000_edge_data){
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+        edge_map <- edge_mapping_info(expanded_edges)
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+        if (graph_title == "default"){
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+            graph_title <- paste0("Pathway = ", pathwayid, ":",
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+                            KGML@pathwayInfo@title, "Refined by Cell-Line:  ",
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+                            cell_line)
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+        }
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+    }
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+    if (nrow(expanded_edges[expanded_edges$type == "maplink",]) ==
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+        nrow(expanded_edges) & only_mapped) {
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+            edge_map <- edge_mapping_info(expanded_edges)
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+            if (graph_title == "default"){
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+                graph_title <- paste0("Pathway = ", pathwayid, ":",
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+                            KGML@pathwayInfo@title, "Cell-Line: ",
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+                            cell_line,  "  *No Edges in Data")
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+            }
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+        warning("All documented edges are of type 'maplink';
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+            Overlap data cannot be mapped to selected pathway")
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+    }
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+    if(!is.na(cell_line) & add_L1000_edge_data) {
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+        user_data <- overlap_info(KGML, KEGG_mappings, cell_line,
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+                                data_type = data_type, pert_time = pert_time)
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+        if (!is.na(user_data)[1,1]) {
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+            edges_plus_data <- add_edge_data(expanded_edges, KEGG_mappings,
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+                                            user_data, c(10,12),
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+                                            only_mapped = only_mapped)
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+            edge_map <- edge_mapping_info(edges_plus_data, data_added = TRUE,
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+                                    significance_markup = significance_markup)
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+            if (graph_title == "default"){
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+                graph_title <- paste0("Pathway = ", pathwayid, ":",
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+                                KGML@pathwayInfo@title, ",  Cell-Line: ",
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+                                cell_line, ",  Data type: ", data_type)
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+            }
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+        }
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+        else {
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+            edge_map <- edge_mapping_info(expanded_edges)
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+            if (graph_title == "default"){
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+                graph_title <- paste0("Pathway = ", pathwayid, ":",
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+                                KGML@pathwayInfo@title, ",  Cell-Line: ",
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+                                cell_line, "   *No Edges in Data")
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+            }
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+        }
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+    }
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+    if(refine_by_cell_line){
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+        node_map <- node_mapping_info(full_mappings)
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+    }
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+    else{
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+        node_map <- node_mapping_info(KEGG_mappings)
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+    }
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+    graph_object <- get_graph_object(node_map, edge_map,
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+                                    layered_nodes = layered_nodes)
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+    cyto_vis(graph_object, title = graph_title)
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+    if(get_data){
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+        return(edge_map)
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+    }
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+}
R/KEGGlincs.R
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+#' KEGGlincs: an R package designed to explore the edges in KEGG pathways
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+#' @docType package
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+#' @name KEGGlincs
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+
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+NULL
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R/add_edge_data.R
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+#' Annotate KEGG edge mappings with user data
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+#' @description Add data column[s] to object created from function
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+#' expand_KEGG_edges
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+#' @export
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+#' @importFrom gtools smartbind
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+#' @importFrom plyr rename
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+#' @param expanded_edges The data frame object generated via the function
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+#' expand_KEGG_edges
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+#' @param KEGG_mappings KEGG_mappings The data.frame object generated by the
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+#' function expand_KEGG_mappings
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+#' @param user_data A data frame where in which the first two columns contain
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+#' gene symbols representing an edge and any/all other column[s] contain
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+#' corresponding edge data.
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+#' @param data_column_no The column index for desired user data to be added
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+#' @param only_mapped A logical indicator; if set to FALSE will return 'de-novo'
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+#' edges that 'exist' in data but are not documented in KEGG
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+#' @return A data frame object with detailed KEGG edge mappings annotated with
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+#' user data
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+#' @examples
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+#' p53_KGML <- get_KGML('hsa04115')
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+#' p53_KEGG_mappings <- expand_KEGG_mappings(p53_KGML)
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+#' p53_edges <- expand_KEGG_edges(p53_KGML, p53_KEGG_mappings)
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+#' p53_HA1E_data <- overlap_info(p53_KGML, p53_KEGG_mappings, 'HA1E',
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+#'                                data_type = '100_bing', only_mapped = FALSE)
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+#'
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+#' p53_edges_HA1E_ALL <- add_edge_data(p53_edges, p53_KEGG_mappings,
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+#'                                      p53_HA1E_data, c(3, 10,12))
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+#' p53_edges_HA1E_MAPPED <- add_edge_data(p53_edges, p53_KEGG_mappings,
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+#'                                         p53_HA1E_data, c(3, 10,12),
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+#'                                         only_mapped = TRUE)
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+
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+
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+add_edge_data <- function(expanded_edges, KEGG_mappings,
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+                        user_data, data_column_no = 3, only_mapped = FALSE) {
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+
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+    expanded_edges <- expanded_edges[expanded_edges$type != "maplink", ]
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+
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+    if ("pre_mapped" %in% names(user_data)) {
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+        user_data <- user_data[, -c(which(colnames(user_data) == "pre_mapped"))]
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+    }
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+
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+    if (nrow(expanded_edges) > 0) {
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+
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+        expanded_edges$unique_ID = paste0(expanded_edges$entry1symbol, ",",
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+            expanded_edges$entry2symbol)
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+        expanded_edges$unique_IDR = paste0(expanded_edges$entry2symbol, ",",
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+            expanded_edges$entry1symbol)
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+        user_data$unique_ID = paste0(user_data$knockout1, ",",
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+                                        user_data$knockout2)
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+        pre_mapped1 <- subset(user_data, user_data$unique_ID %in%
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+                                    expanded_edges$unique_ID)
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+        pre_mapped2 <- subset(user_data, user_data$unique_ID %in%
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+                                    expanded_edges$unique_IDR)
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+        pre_mapped2 <- pre_mapped2[, c(2, 1, 3:ncol(pre_mapped2))]
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+        names(pre_mapped2) = names(pre_mapped1)
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+        if (nrow(pre_mapped2) >= 1 & nrow(pre_mapped1) >= 1) {
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+            pre_mapped2$unique_ID <- paste0(pre_mapped2$knockout1, ",",
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+                                            pre_mapped2$knockout2)
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+            pre_mapped <- rbind(pre_mapped1, pre_mapped2)
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+        }
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+        if (nrow(pre_mapped2) == 0 & (nrow(pre_mapped1) == 0)) {
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+            pre_mapped <- data.frame(unique_ID = NA)
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+        }
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+        if (nrow(pre_mapped1) == 0 & nrow(pre_mapped2) >= 1) {
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+            pre_mapped2$unique_ID <- paste0(pre_mapped2$knockout1, ",",
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+                                            pre_mapped2$knockout2)
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+            pre_mapped <- pre_mapped2
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+        }
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+        if (nrow(pre_mapped2) == 0 & nrow(pre_mapped1) >= 1) {
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+            pre_mapped <- pre_mapped1
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+        }
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+        if (!is.na(pre_mapped[1, 1])) {
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+            expanded_edges_1 <- subset(expanded_edges, expanded_edges$unique_ID
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+                                        %in% pre_mapped$unique_ID)
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+            expanded_edges_1 <- expanded_edges[expanded_edges$unique_ID %in%
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+                pre_mapped$unique_ID, ]
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+            expanded_edges_2 <- expanded_edges[!expanded_edges$unique_ID %in%
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+                pre_mapped$unique_ID, ]
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+            expanded_edges_1$has_data = 1
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+            testval <- nrow(expanded_edges_2)
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+            if (testval > 0) {
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+                expanded_edges_2$has_data = 0
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+                edge_set <- rbind(expanded_edges_1, expanded_edges_2)
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+            } else {
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+                edge_set <- expanded_edges_1
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+            }
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+
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+            edge_set <- edge_set[order(edge_set$unique_ID), ]
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+
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+            data_to_add <- cbind(as.character(pre_mapped[, "unique_ID"]),
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+                                pre_mapped[, data_column_no])
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+            data_to_add <- data.frame(data_to_add, stringsAsFactors = FALSE)
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+            names(data_to_add)[1] <- "unique_ID"
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+            if (ncol(data_to_add) == 2) {
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+                names(data_to_add)[2] <- names(pre_mapped)[data_column_no]
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+            }
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+
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+            data_to_add <- data_to_add[order(data_to_add$unique_ID), ]
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+
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+            annotated_edges <- merge(edge_set, data_to_add, "unique_ID",
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+                                     all.x = TRUE)
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+            drops <- c("unique_ID", "unique_IDR")
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+            annotated_edges <- annotated_edges[, !(names(annotated_edges) %in%
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+                drops)]
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+            cat(paste0("Number of edges documented in selected pathway = ",
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+                nrow(annotated_edges)), "\n")
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+            cat(paste0("Number of edges with corresponding user data = ",
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+                        sum(annotated_edges$has_data), "\n"))
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+            cat(paste0("Coverage = ", round(sum(annotated_edges$has_data)/
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+                        nrow(annotated_edges) * 100, 2), "%", "\n"))
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+            annotated_edges$premapped <- 1
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+            un_mapped <- subset(user_data, !user_data$unique_ID %in%
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+                                expanded_edges$unique_ID &
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+                            !user_data$unique_ID %in% expanded_edges$unique_IDR)
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+            un_mapped_edges <- un_mapped[, c(1:2, data_column_no,
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+                                            ncol(un_mapped))]
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+
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+            if (only_mapped) {
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+                return(annotated_edges)
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+            }
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+        } else {
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+            annotated_edges <- expanded_edges
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+            annotated_edges$premapped <- 1
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+            annotated_edges$has_data <- 0
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+            un_mapped <- user_data
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+            un_mapped$unique_ID <- paste0(un_mapped$knockout1,
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+                                        un_mapped$knockout2)
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+            un_mapped_edges <- un_mapped[, c(1:2, data_column_no,
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+                                            ncol(un_mapped))]
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+            un_mapped_edges$premapped <- 0
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+            un_mapped_edges$has_data <- 0
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+            cat(paste0("Number of edges documented in selected pathway = ",
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+                nrow(annotated_edges)), "\n")
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+            cat(paste0("Number of edges with corresponding user data = ",
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+                        sum(annotated_edges$has_data), "\n"))
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+            cat(paste0("Coverage = ", round(sum(annotated_edges$has_data)/
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+                        nrow(annotated_edges) * 100, 2), "%", "\n"))
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+            if (only_mapped) {
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+                cat(paste0("No documented edges are found in data;
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+                    only data for de-novo edges can be mapped \n"))
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+                return(annotated_edges)
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+            }
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+        }
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+    } else if (nrow(expanded_edges) == 0) {
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+        annotated_edges <- expanded_edges
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+        annotated_edges$premapped <- 1
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+        annotated_edges$has_data <- 0
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+        un_mapped <- user_data
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+        un_mapped$unique_ID <- paste0(un_mapped$knockout1, un_mapped$knockout2)
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+        un_mapped_edges <- un_mapped[, c(1:2, data_column_no, ncol(un_mapped))]
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+        un_mapped_edges$premapped <- 0
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+        un_mapped_edges$has_data <- 0
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+        cat(paste0("Number of edges documented in selected pathway = ",
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+                    nrow(annotated_edges)), "\n")
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+        cat(paste0("Number of edges with corresponding user data = ",
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+                    sum(annotated_edges$has_data), "\n"))
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+        cat(paste0("Coverage = ", round(sum(annotated_edges$has_data)/
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+                    nrow(annotated_edges) * 100, 2), "%", "\n"))
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+        if (only_mapped) {
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+            return(annotated_edges)
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+        }
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+    }
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+    names(un_mapped_edges)[1:2] <- c("entryNAME_1", "entryNAME_2")
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+    for (i in 1:nrow(un_mapped_edges)) {
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+        un_mapped_edges$Source_eid[i] <-
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+            list(KEGG_mappings$entryID[which(KEGG_mappings$entrySYMBOL ==
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+            un_mapped_edges$entryNAME_1[i])])
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+        un_mapped_edges$Target_eid[i] <-
169 
+            list(KEGG_mappings$entryID[which(KEGG_mappings$entrySYMBOL ==
170 
+            un_mapped_edges$entryNAME_2[i])])
171 
+        x <- length(unlist(un_mapped_edges$Source_eid[i]))
172 
+        y <- length(unlist(un_mapped_edges$Target_eid[i]))
173 
+        if (x > 1 | y > 1) {
174 
+            un_mapped_edges$simple[i] <- FALSE
175 
+        } else {
176 
+            un_mapped_edges$simple[i] <- TRUE
177 
+        }
178 
+    }
179 
+    simple_un_mapped_edges <- un_mapped_edges[un_mapped_edges$simple == TRUE,
180 
+        -ncol(un_mapped_edges)]
181 
+    complex_un_mapped_edges <- un_mapped_edges[un_mapped_edges$simple == FALSE,
182 
+        -ncol(un_mapped_edges)]
183 
+    test_val <- nrow(complex_un_mapped_edges)
184 
+    if (test_val == 0) {
185 
+        un_mapped_edges <- simple_un_mapped_edges
186 
+    } else {
187 
+        keeps <- c("Source_eid", "Target_eid", "unique_ID")
188 
+        c_temp <- complex_un_mapped_edges[, (names(complex_un_mapped_edges) %in%
189 
+            keeps)]
190 
+
191 
+        for (i in 1:nrow(c_temp)) {
192 
+            x <- length(unlist(c_temp$Source_eid[i]))
193 
+            y <- length(unlist(c_temp$Target_eid[i]))
194 
+            l <- x * y
195 
+
196 
+            c_temp$Source_eid[i] <- list(sort(unlist(rep(c_temp$Source_eid[i],
197 
+                y))))
198 
+            c_temp$Target_eid[i] <- list(unlist(rep(c_temp$Target_eid[i], x)))
199 
+            c_temp$unique_ID[i] <- list(rep(c_temp$unique_ID[i], l))
200 
+        }
201 
+
202 
+        c_temp <- data.frame(unique_ID = unlist(c_temp$unique_ID), Source_eid =
203 
+                            unlist(c_temp$Source_eid),
204 
+                            Target_eid = unlist(c_temp$Target_eid))
205 
+        drops <- c("Source_eid", "Target_eid")
206 
+        complex_un_mapped_edges <-
207 
+            complex_un_mapped_edges[, !(names(complex_un_mapped_edges) %in%
208 
+            drops)]
209 
+        complex_un_mapped_edges <- merge(complex_un_mapped_edges, c_temp)
210 
+        un_mapped_edges <- rbind(simple_un_mapped_edges,
211 
+                                 complex_un_mapped_edges)
212 
+    }
213 
+    un_mapped_edges$Source_eid <- unlist(un_mapped_edges$Source_eid)
214 
+    un_mapped_edges$Target_eid <- unlist(un_mapped_edges$Target_eid)
215 
+    un_mapped_edges <- plyr::rename(un_mapped_edges, c(Source_eid = "entry1",
216 
+        Target_eid = "entry2", entryNAME_1 = "entry1symbol",
217 
+        entryNAME_2 = "entry2symbol"))
218 
+    un_mapped_edges$subtype1 <- "de_novo"
219 
+
220 
+    drops <- c("unique_ID")
221 
+    un_mapped_edges <- un_mapped_edges[, !(names(un_mapped_edges) %in% drops)]
222 
+    un_mapped_edges$has_data <- 1
223 
+    un_mapped_edges$premapped <- 0
224 
+    for (i in 1:nrow(un_mapped_edges)) {
225 
+        un_mapped_edges$entry1accession[i] <-
226 
+            KEGG_mappings$entryACCESSION[which(KEGG_mappings$entrySYMBOL ==
227 
+            un_mapped_edges$entry1symbol[i])][1]
228 
+        un_mapped_edges$entry2accession[i] <-
229 
+            KEGG_mappings$entryACCESSION[which(KEGG_mappings$entrySYMBOL ==
230 
+            un_mapped_edges$entry2symbol[i])][1]
231 
+        un_mapped_edges$entry1type[i] <-
232 
+            KEGG_mappings$entryTYPE[which(KEGG_mappings$entrySYMBOL ==
233 
+            un_mapped_edges$entry1symbol[i])][1]
234 
+        un_mapped_edges$entry2type[i] <-
235 
+            KEGG_mappings$entryTYPE[which(KEGG_mappings$entrySYMBOL ==
236 
+            un_mapped_edges$entry2symbol[i])][1]
237 
+    }
238 
+
239 
+    if (nrow(annotated_edges) > 0 & nrow(un_mapped_edges) > 0) {
240 
+        all_edges <- gtools::smartbind(annotated_edges, un_mapped_edges)
241 
+    } else if (nrow(annotated_edges) > 0)
242 
+        all_edges <- annotated_edges else {
243 
+        all_edges <- un_mapped_edges
244 
+        all_edges$value <- NA
245 
+        all_edges$subtype2 <- NA
246 
+        all_edges$value2 <- NA
247 
+        all_edges$specific_subtype <- NA
248 
+        all_edges$type <- NA
249 
+        all_edges$is_direct <- 1
250 
+        all_edges$edgeID <- seq(1:nrow(un_mapped_edges))
251 
+        refcols <- c("edgeID", "entry1accession", "entry2accession", "entry1",
252 
+            "entry2")
253 
+        all_edges <- all_edges[, c(refcols, setdiff(names(all_edges), refcols))]
254 
+        cat(paste0("All documented edges are of type maplink; only data for
255 
+                    de-novo edges can be mapped \n"))
256 
+    }
257 
+
258 
+    for (i in 1:nrow(all_edges)) {
259 
+        if (all_edges$entry1[i] == all_edges$entry2[i]) {
260 
+            all_edges$paralogs[i] <- 1
261 
+        } else {
262 
+            all_edges$paralogs[i] <- 0
263 
+        }
264 
+    }
265 
+    return(all_edges)
266 
+}
R/cyto_vis.R
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1 
+#' Send graph to Cytoscape via CyREST
2 
+#' @description View the KEGG pathway in Cytoscape. With either the
3 
+#' 'expanded edges' or 'stacked nodes' layout, users can visualize and interact
4 
+#' with the graphs [strictly] as they are documented in the most recent KGML
5 
+#' available from KEGG.
6 
+#' This function is a modified version of the function send2cy(),
7 
+#'  which is part of the cyREST utility functions.
8 
+#' @export
9 
+#' @import methods
10 
+#' @import httr
11 
+#' @import RJSONIO
12 
+#' @param graph_object An igraph object such as the one generated by the
13 
+#' function \code{\link{get_graph_object}}
14 
+#' @param title An optional title for the graph when it is in Cytoscape
15 
+#' @param edge_width_attribute The attribute that will be used for edge width;
16 
+#' if data is not added or the attribute is not part of the graphing
17 
+#' information, the edge width will default to 1.
18 
+#' @param port.number The port address for Cytoscape
19 
+#' @return A dynamic map in Cytoscape automatically formatted for convenient
20 
+#' viewing.
21 
+#' @examples
22 
+#' p53_KGML <- get_KGML("hsa04115")
23 
+#' p53_KEGG_mappings <- expand_KEGG_mappings(p53_KGML, FALSE)
24 
+#' nodes <- node_mapping_info(p53_KEGG_mappings)
25 
+#'
26 
+#' p53_edges <- expand_KEGG_edges(p53_KGML, p53_KEGG_mappings)
27 
+#' edges <- edge_mapping_info(p53_edges)
28 
+#'
29 
+#' p53_graph_object <- get_graph_object(nodes, edges)
30 
+#'
31 
+#' @examples \dontrun{
32 
+#' cyto_vis(p53_graph_object, "Default p53 Graph [no data added]")
33 
+#'
34 
+#' #Workflow to visualize graph with data-dependent attributes:
35 
+#'
36 
+#' p53_KGML <- get_KGML("hsa04115")
37 
+#' p53_KEGG_mappings <- expand_KEGG_mappings(p53_KGML)
38 
+#' nodes <- node_mapping_info(p53_KEGG_mappings)
39 
+#'
40 
+#' p53_edges <- expand_KEGG_edges(p53_KGML, p53_KEGG_mappings)
41 
+#'
42 
+#' p53_HA1E_data <- overlap_info(p53_KGML, p53_KEGG_mappings, "HA1E",
43 
+#'                                data_type = "100_bing")
44 
+#' p53_edges_plus_data <- add_edge_data(p53_edges, p53_KEGG_mappings,
45 
+#'                                       p53_HA1E_data, c(3, 10,12),
46 
+#'                                       only_mapped = TRUE)
47 
+#'
48 
+#' edges <- edge_mapping_info(p53_edges_plus_data, data_added = TRUE)
49 
+#'
50 
+#' p53_plus_data_graph_object <- get_graph_object(nodes, edges)
51 
+#'
52 
+#' cyto_vis(p53_plus_data_graph_object, "p53 Graph: Mapped Edges + HA1E Data",
53 
+#'          edge_width_attribute = "UP")
54 
+#'          }
55 
+
56 
+cyto_vis <-
57 
+    function(graph_object, title = "Cytoscape Graph Window",
58 
+            edge_width_attribute = "summary_score",
59 
+            port.number = 1234) {
60 
+    base.url = paste("http://localhost:", toString(port.number), "/v1", sep="")
61 
+
62 
+    if (edge_width_attribute %in% names(igraph::edge_attr(graph_object))){
63 
+        min.summary_score <- min(abs(igraph::E(graph_object)$summary_score),
64 
+                                na.rm = TRUE)
65 
+        max.summary_score <- max(abs(igraph::E(graph_object)$summary_score),
66 
+                                na.rm = TRUE)
67 
+        map_edge_width <- TRUE
68 
+    }
69 
+    else {
70 
+        min.summary_score <- NA
71 
+        max.summary_score <- NA
72 
+        map_edge_width <- FALSE
73 
+    }
74 
+
75 
+    graph_object$name <- title
76 
+    cygraph <- toCytoscape(graph_object)
77 
+
78 
+    network.url = paste(base.url, "networks", sep="/")
79 
+    res <- httr::POST(url=network.url, body=cygraph, encode="json")
80 
+    network.suid = unname(RJSONIO::fromJSON(rawToChar(res$content)))
81 
+
82 
+    style.name = "myKEGGstyle"
83 
+    mappings <- generate_mappings(style.name, map_edge_width,
84 
+                                    edge_width_attribute,
85 
+                                    min_score = min.summary_score,
86 
+                                    max_score = max.summary_score)
87 
+    style.url = paste(base.url, "styles", sep="/")
88 
+    style <- list(title=style.name, defaults = mappings[[1]],
89 
+                  mappings = mappings[[2]])
90 
+    style.JSON <- RJSONIO::toJSON(style)
91 
+    httr::POST(url=style.url, body=style.JSON, encode = "json")
92 
+    apply.style.url = paste(base.url, "apply/styles", style.name ,
93 
+                            toString(network.suid), sep="/")
94 
+    httr::GET(apply.style.url)
95 
+    }
R/edge_mapping_info.R
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1 
+#' Prepare edges for mapping
2 
+#' @description Modify the mapping information for desired look when graphed in
3 
+#'  Cytoscape
4 
+#' @param expanded_edges The data frame object generated via the function
5 
+#' expand_KEGG_edges() OR has been modified by the function add_edge_data()
6 
+#' @param data_added A logical indicator; must be set to TRUE if user data has
7 
+#'  been added (i.e. edges modified by function add_edge_data())
8 
+#' @param significance_markup A logical indicator; if set to TRUE will color
9 
+#' edges based on direction and significance of correlation (as determined by
10 
+#' user-data-analysis)
11 
+#' @return A data.frame object for edges that will be passed on to the function
12 
+#' get_graph_object
13 
+#' @export
14 
+#' @examples
15 
+#' p53_KGML <- get_KGML("hsa04115")
16 
+#' p53_KEGG_mappings <- expand_KEGG_mappings(p53_KGML)
17 
+#'
18 
+#' #Default; no data added to edges:
19 
+#'
20 
+#' p53_edges <- expand_KEGG_edges(p53_KGML, p53_KEGG_mappings)
21 
+#' p53_edge_mapping_info <- edge_mapping_info(p53_edges)
22 
+#'
23 
+#' #If data is added to edges as additional attribute[s]:
24 
+#'
25 
+#' p53_HA1E_data <- overlap_info(p53_KGML, p53_KEGG_mappings,
26 
+#'                                "HA1E", data_type = "100_bing")
27 
+#'
28 
+#' p53_edges_HA1E_data_MAPPED <- add_edge_data(p53_edges, p53_KEGG_mappings,
29 
+#'                                                p53_HA1E_data, c(3, 10,12),
30 
+#'                                                only_mapped = TRUE)
31 
+#'
32 
+#' p53_edge_mapping_HA1E <- edge_mapping_info(p53_edges_HA1E_data_MAPPED,
33 
+#'                                                       data_added = TRUE)
34 
+#'
35 
+
36 
+edge_mapping_info <-
37 
+function(expanded_edges, data_added = FALSE, significance_markup = FALSE){
38 
+    expanded_edges <- expanded_edges[,-c(1)]
39 
+    for(i in 1:nrow(expanded_edges)){
40 
+        if (expanded_edges$subtype1[i] == "activation"){
41 
+            expanded_edges$color[i] = "#b20000"
42 
+        }
43 
+        else if (expanded_edges$subtype1[i] =="expression"){
44 
+            expanded_edges$color[i] = "#b20000"
45 
+        }
46 
+        else if (expanded_edges$subtype1[i] =="inhibition"){
47 
+            expanded_edges$color[i] = "#0015b2"
48 
+        }
49 
+        else if (expanded_edges$subtype1[i] =="irreversible"){
50 
+          expanded_edges$color[i] = "#b20000"
51 
+        }
52 
+        else if (expanded_edges$subtype1[i] =="repression"){
53 
+             expanded_edges$color[i] = "#0015b2"
54 
+        }
55 
+        else if (expanded_edges$subtype1[i] == "compound" |
56 
+                    expanded_edges$subtype1[i] == "indirect_effect" |
57 
+                    expanded_edges$subtype1[i] == "binding_association"){
58 
+             expanded_edges$color[i] = "#000000"
59 
+        }
60 
+        else if (expanded_edges$subtype1[i] == "de_novo") {
61 
+          expanded_edges$color[i] = "#808080"
62 
+        }
63 
+        else if (expanded_edges$subtype1[i] == "Not defined in KEGG" |
64 
+                    expanded_edges$type[i] == "dummy") {
65 
+             expanded_edges$color[i] = "#808080"
66 
+        }
67 
+        else {
68 
+             expanded_edges$color[i] = "#1c9900"
69 
+        }
70 
+
71 
+        if (expanded_edges$color[i] == "#1c9900"){
72 
+             expanded_edges$edge_label[i] = expanded_edges$value[i]
73 
+        }
74 
+        else {
75 
+             expanded_edges$edge_label[i] = NA
76 
+        }
77 
+
78 
+        if (is.na(expanded_edges$subtype2[i]) == FALSE &
79 
+            expanded_edges$subtype2[i] != "indirect"){
80 
+                if (expanded_edges$subtype1[i] == "inhibition"){
81 
+                    expanded_edges$color[i] = "#690099"
82 
+                }
83 
+                else if (expanded_edges$subtype1[i] == "activation"){
84 
+                    expanded_edges$color[i] = "#FF6600"
85 
+                }
86 
+            expanded_edges$edge_label[i] = expanded_edges$value2[i]
87 
+        }
88 
+        if(data_added){
89 
+            if (expanded_edges$premapped[i] == 1){
90 
+                if (expanded_edges$value[i] == "--|"){
91 
+                    expanded_edges$tooltip[i] <-
92 
+                        paste0(expanded_edges$entry1symbol[i]," --| ",
93 
+                                expanded_edges$entry2symbol[i])
94 
+                    }
95 
+                else {
96 
+                    expanded_edges$tooltip[i] <-
97 
+                        paste0(expanded_edges$entry1symbol[i], " --> ",
98 
+                                expanded_edges$entry2symbol[i])
99 
+                }
100 
+            }
101 
+          else {
102 
+            expanded_edges$tooltip[i] <- paste0(expanded_edges$entry1symbol[i],
103 
+                                                " - ",
104 
+                                                expanded_edges$entry2symbol[i])
105 
+            }
106 
+        }
107 
+        else {
108 
+            if (expanded_edges$value[i] == "--|"){
109 
+                expanded_edges$tooltip[i] <-
110 
+                    paste0(expanded_edges$entry1symbol[i], " --| ",
111 
+                                                expanded_edges$entry2symbol[i])
112 
+                }
113 
+            else {
114 
+                expanded_edges$tooltip <-
115 
+                    paste0(expanded_edges$entry1symbol, " --> ",
116 
+                                                expanded_edges$entry2symbol)
117 
+            }
118 
+        }
119 
+    }
120 
+
121 
+    expanded_edges$name <- paste0(expanded_edges$entry1,
122 
+                                " (", expanded_edges$type, ") ",
123 
+                                expanded_edges$entry2)
124 
+    if (significance_markup){
125 
+        for (i in 1:nrow(expanded_edges)){
126 
+            if (expanded_edges$has_data[i] == 1){
127 
+                if (expanded_edges$summary_score[i] > 0 &
128 
+                    expanded_edges$significant[i] == 1){
129 
+                        expanded_edges$color[i] <- "#b20000"
130 
+                        }
131 
+                else if (expanded_edges$summary_score[i] > 0 &
132 
+                        expanded_edges$significant[i] == 0){
133 
+                        expanded_edges$color[i] <- "#FF6600"
134 
+                        }
135 
+                else if (expanded_edges$summary_score[i] <= 0 &
136 
+                        expanded_edges$significant[i] == 1){
137 
+                        expanded_edges$color[i] <- "#0015b2"
138 
+                        }
139 
+                else {
140 
+                        expanded_edges$color[i] <- "#690099"
141 
+                }
142 
+            }
143 
+            else {
144 
+                expanded_edges$color[i] = "#808080"
145 
+            }
146 
+        }
147 
+    }
148 
+    expanded_edges <- expanded_edges[,c(3:4, 1:2, 5:ncol(expanded_edges))]
149 
+    return(expanded_edges)
150 
+}
R/expand_KEGG_edges.R
History View file @ 4614338
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1 
+#' Get detailed KEGG mapping information for each relation [edge] documented
2 
+#' in KEGG
3 
+#' @description Extract relationship information from KGML object and re-map
4 
+#'  based on normalized node information
5 
+#'
6 
+#' @param KGML_file An object of formal class KEGGPathway
7 
+#' @param KEGG_mappings The data.frame object generated by the function
8 
+#' expand_KEGG_mappings
9 
+#'
10 
+#' @return A dataframe object with unique entry information for all edges
11 
+#' documented in the KEGG pathway.
12 
+#'         Note that each row has a unique combination of values for
13 
+#'          (entry1, entry2, entry1symbol, entry2symbol).
14 
+#' @export
15 
+#' @importMethodsFrom KEGGgraph edges
16 
+#' @examples
17 
+#' p53_KGML <- get_KGML("hsa04115")
18 
+#' p53_KEGG_mappings <- expand_KEGG_mappings(p53_KGML, FALSE)
19 
+#' p53_edges <- expand_KEGG_edges(p53_KGML, p53_KEGG_mappings)
20 
+
21 
+
22 
+expand_KEGG_edges <-
23 
+function(KGML_file,KEGG_mappings){
24 
+    num_edges <- length(KGML_file@edges)
25 
+    if (num_edges == 0){
26 
+        print("No Documented Edges in Pathway")
27 
+        expanded_edges <- data.frame("edgeID"=1, "entry1"= "1", "entry2" = "1",
28 
+                                    "entry1accession"="dummy",  "
29 
+                                    entry2accession"="dummy",
30 
+                                    "type"= "dummy", "subtype1"="dummy",
31 
+                                    "value"="dummy", "subtype2" = "dummy",
32 
+                                    "value2" = "dummy",
33 
+                                    "specific_subtype"="dummy",
34 
+                                    "is_direct"= 0, "entry1type"="dummy",
35 
+                                    "entry2type"= "dummy", "entry1symbol"= "1",
36 
+                                    "entry2symbol"="1",
37 
+                                    stringsAsFactors = FALSE)
38 
+    return(expanded_edges)
39 
+    }
40 
+    map_edge_data<- KGML_file@edges
41 
+    get_edges<- data.frame(edgeID = seq(1:length(map_edge_data )))
42 
+    for (i in 1:nrow(get_edges)){
43 
+        get_edges$entry1[i] <- as.numeric(map_edge_data[[i]]@entry1ID)
44 
+        get_edges$entry2[i] <- as.numeric(map_edge_data[[i]]@entry2ID)
45 
+        get_edges$type[i] <- map_edge_data[[i]]@type
46 
+        if (length(map_edge_data[[i]]@subtype) == 1){
47 
+            get_edges$subtype1[i] <- map_edge_data[[i]]@subtype[[1]]@name
48 
+            if (get_edges$subtype1[i] == "binding/association"){
49 
+                get_edges$subtype1[i] <- "binding_association"
50 
+                }
51 
+            get_edges$value[i] <- map_edge_data[[i]]@subtype[[1]]@value
52 
+            get_edges$subtype2[i] <- NA
53 
+            get_edges$value2[i] <- NA
54 
+            get_edges$specific_subtype[i] <- get_edges$subtype1[i]
55 
+            get_edges$is_direct[i] <- 1
56 
+            if (get_edges$subtype1[i] == "indirect effect"){
57 
+                get_edges$is_direct[i] <- 0
58 
+                get_edges$subtype1[i] <- "indirect_effect"
59 
+            }
60 
+        }
61 
+        else if (length(map_edge_data[[i]]@subtype) == 2){
62 
+            get_edges$subtype1[i] <- map_edge_data[[i]]@subtype[[1]]@name
63 
+                if (get_edges$subtype1[i] == "binding/association"){
64 
+                    get_edges$subtype1[i] <- "binding_association"
65 
+                    }
66 
+            get_edges$value[i] <- map_edge_data[[i]]@subtype[[1]]@value
67 
+            get_edges$subtype2[i] <- map_edge_data[[i]]@subtype[[2]]@name
68 
+            get_edges$specific_subtype[i] <- paste0(get_edges$subtype1[i], "_",
69 
+                                                    get_edges$subtype2[i])
70 
+            get_edges$value2[i] <- map_edge_data[[i]]@subtype[[2]]@value
71 
+            get_edges$is_direct[i] <- 1
72 
+            if (get_edges$subtype2[i] == "indirect effect"){
73 
+                get_edges$subtype2[i] <- "indirect"
74 
+                get_edges$is_direct[i] <- 0
75 
+            }
76 
+        }
77 
+        else {
78 
+            get_edges$subtype1[i] <- "Not defined in KEGG"
79 
+            get_edges$value[i] <- "Not defined in KEGG"
80 
+            get_edges$subtype2[i] <- NA
81 
+            get_edges$value2[i] <- NA
82 
+            get_edges$specific_subtype[i] <- NA
83 
+            get_edges$is_direct[i] <- 1
84 
+        }
85 
+        get_edges$entry1type[i] <-
86 
+            KEGG_mappings$entryTYPE[which(KEGG_mappings$entryID ==
87 
+                                         get_edges$entry1[i])][1]
88 
+        get_edges$entry2type[i] <-
89 
+            KEGG_mappings$entryTYPE[which(KEGG_mappings$entryID ==
90 
+                                         get_edges$entry2[i])][1]
91 
+    }
92 
+    get_edges <- get_edges[!is.na(get_edges$entry1type) &
93 
+                            !is.na(get_edges$entry2type),]
94 
+    if (nrow(get_edges) ==0){
95 
+        print("No Documented Edges in Pathway for selected cell type;
96 
+            all edges are between non-expressed genes")
97 
+        expanded_edges <- data.frame("edgeID"=1, "entry1"= "1", "entry2" = "1",
98 
+                                     "entry1accession"="dummy",
99 
+                                    "entry2accession"="dummy","type"= "dummy",
100 
+                                    "subtype1"="dummy", "value"="dummy",
101 
+                                    "subtype2" = "dummy", "value2" = "dummy",
102 
+                                    "specific_subtype"="dummy", "is_direct"= 0,
103 
+                                    "entry1type"="dummy",
104 
+                                    "entry2type"= "dummy","entry1symbol"= "1",
105 
+                                    "entry2symbol"="1",
106 
+                                    stringsAsFactors = FALSE)
107 
+        return(expanded_edges)
108 
+    }
109 
+
110 
+  ##At some point include option not to ungroup edges
111 
+    edges_no_groups <- subset(get_edges, get_edges$entry1type != "group"
112 
+                            & get_edges$entry2type != "group", select = -c(1))
113 
+    edges_with_groups <- subset(get_edges, get_edges$entry1type == "group" |
114 
+                                get_edges$entry2type == "group")
115 
+    edges_one_group <- subset(get_edges, get_edges$entry1type == "group" &
116 
+                                !get_edges$entry2type == "group" |
117 
+                                get_edges$entry2type == "group" &
118 
+                                !get_edges$entry1type == "group")
119 
+    edges_two_groups <- subset(get_edges, get_edges$entry1type == "group" &
120 
+                                get_edges$entry2type == "group")
121 
+    if (nrow(edges_with_groups) > 0){
122 
+        if (nrow(edges_one_group) > 0){
123 
+            edges_one_group$entry1all <- NA
124 
+            edges_one_group$entry2all <- NA
125 
+            for (i in 1:nrow(edges_one_group)){
126 
+                if (edges_one_group$entry1type[i] == "group"){
127 
+                    edges_one_group$entry1all[i] <-
128 
+                    KEGG_mappings$groupMEMBERS[which(KEGG_mappings$entryID ==
129 
+                                                edges_one_group$entry1[i])]
130 
+                    l <- length(unlist(edges_one_group$entry1all[i]))
131 
+                    edges_one_group$entry2all[i] <-
132 
+                        list(as.character(rep(edges_one_group$entry2[i], l)))
133 
+                    }
134 
+                else if (edges_one_group$entry2type[i] == "group"){
135 
+                    edges_one_group$entry2all[i] <-
136 
+                    KEGG_mappings$groupMEMBERS[which(KEGG_mappings$entryID ==
137 
+                                                edges_one_group$entry2[i])]
138 
+                    l = length(unlist(edges_one_group$entry2all[i]))
139 
+                    edges_one_group$entry1all[i] <-
140 
+                        list(as.character(rep(edges_one_group$entry1[i], l)))
141 
+                    }
142 
+            l = length(unlist(edges_one_group$entry1all[i]))
143 
+            edges_one_group$edgeID_list[i] <-
144 
+                list(rep(edges_one_group$edgeID[i],l))
145 
+            }
146 
+            ewg_temp <- data.frame("edgeID" =
147 
+                                        unlist(edges_one_group$edgeID_list),
148 
+                            "entry1" = unlist(edges_one_group$entry1all),
149 
+                            "entry2" = unlist(edges_one_group$entry2all),
150 
+                            stringsAsFactors = FALSE)
151 
+            edges_one_group <- edges_one_group[,-c(2:3, 13:15)]
152 
+            edges_one_group <- merge(ewg_temp,edges_one_group, by = "edgeID")
153 
+            edges_one_group <- edges_one_group[,-c(1)]
154 
+        }
155 
+        if (nrow(edges_two_groups) > 0){
156 
+            edges_two_groups$entry1all <- NA
157 
+            edges_two_groups$entry2all <- NA
158 
+                for (i in 1:nrow(edges_two_groups)){
159 
+                    edges_two_groups$entry1all[i] <-
160 
+                    KEGG_mappings$groupMEMBERS[which(KEGG_mappings$entryID ==
161 
+                                                edges_two_groups$entry1[i])]
162 
+                    edges_two_groups$entry2all[i] <-
163 
+                    KEGG_mappings$groupMEMBERS[which(KEGG_mappings$entryID ==
164 
+                                                edges_two_groups$entry2[i])]
165 
+                    x <- length(unlist(edges_two_groups$entry1all[i]))
166 
+                    y <- length(unlist(edges_two_groups$entry2all[i]))
167 
+                    if (x == 1 & y >1){
168 
+                        edges_two_groups$entry1all[i] <-
169 
+                            list(rep(edges_two_groups$entry1all[i], y))
170 
+                        }
171 
+                    else if (x > 1 & y == 1){
172 
+                        edges_two_groups$entry2all[i] <-
173 
+                            list(rep(edges_two_groups$entry2all[i], x))
174 
+                        }
175 
+                    else if (x > 1 & y > 1){
176 
+                        edges_two_groups$entry1all[i] <-
177 
+                            list(rep(edges_two_groups$entry1all[i],y))
178 
+                        edges_two_groups$entry1all[i] <-
179 
+                            list(unlist(edges_two_groups$entry1all[i])[
180 
+                            sort.list(unlist(edges_two_groups$entry1all[i]))])
181 
+                        edges_two_groups$entry2all[i] <-
182 
+                            list(rep(edges_two_groups$entry2all[i],x))
183 
+                    }
184 
+                    l <- length(unlist(edges_two_groups$entry1all[i]))
185 
+                    edges_two_groups$edgeID_list[i] <-
186 
+                        list(rep(edges_two_groups$edgeID[i],l))
187 
+                    }
188 
+            ewg_temp <- data.frame("edgeID" =
189 
+                                    unlist(edges_two_groups$edgeID_list),
190 
+                                "entry1" = unlist(edges_two_groups$entry1all),
191 
+                                "entry2" = unlist(edges_two_groups$entry2all),
192 
+                                stringsAsFactors = FALSE)
193 
+            edges_two_groups <- edges_two_groups[,-c(2:3, 13:15)]
194 
+            edges_two_groups <- merge(ewg_temp,edges_two_groups, by = "edgeID")
195 
+            edges_two_groups <- edges_two_groups[,-c(1)]
196 
+        }
197 
+        if (nrow(edges_one_group) > 0 & nrow(edges_two_groups) > 0){
198 
+            all_edges <- rbind(edges_no_groups, edges_one_group,
199 
+                                edges_two_groups)
200 
+        }
201 
+        else if (nrow(edges_one_group) > 0){
202 
+            all_edges <- rbind(edges_no_groups, edges_one_group)
203 
+        }
204 
+        else if (nrow(edges_two_groups) > 0){
205 
+             all_edges <- rbind(edges_no_groups, edges_two_groups)
206 
+        }
207 
+    }
208 
+    else {
209 
+        all_edges <- edges_no_groups
210 
+    }
211 
+    for (i in 1:nrow(all_edges)){
212 
+        all_edges$entry1all_accession[i] <-
213 
+            list(KEGG_mappings$entryACCESSION[which(KEGG_mappings$entryID ==
214 
+                                                all_edges$entry1[i])])
215 
+        all_edges$entry2all_accession[i] <-
216 
+            list(KEGG_mappings$entryACCESSION[which(KEGG_mappings$entryID ==
217 
+                                                all_edges$entry2[i])])
218 
+        x <- length(unlist(all_edges$entry1all_accession[i]))
219 
+        y <- length(unlist(all_edges$entry2all_accession[i]))
220 
+        if (x == 1 & y >1){
221 
+            all_edges$entry1all_accession[i] <-
222 
+                list(rep(all_edges$entry1all_accession[i], y))
223 
+            }
224 
+        else if (x > 1 & y == 1) {
225 
+            all_edges$entry2all_accession[i] <-
226 
+                list(rep(all_edges$entry2all_accession[i], x))
227 
+        }
228 
+        else if (x > 1 & y > 1) {
229 
+            all_edges$entry1all_accession[i] <-
230 
+                list(rep(all_edges$entry1all_accession[i],y))
231 
+            all_edges$entry1all_accession[i] <-
232 
+                list(unlist(all_edges$entry1all_accession[i])[sort.list(unlist(
233 
+                    all_edges$entry1all_accession[i]))])
234 
+            all_edges$entry2all_accession[i] <-
235 
+                list(rep(all_edges$entry2all_accession[i],x))
236 
+            }
237 
+        l <- length(unlist(all_edges$entry1all_accession[i]))
238 
+        all_edges$edgeID[i] = list(rep(i,l))
239 
+    }
240 
+    for (i in 1:nrow(all_edges)){
241 
+        all_edges$l1[i] <- length(all_edges$entry1all_accession[[i]])
242 
+        all_edges$l2[i] <- length(all_edges$entry2all_accession[[i]])
243 
+    }
244 
+    all_edges <- all_edges[all_edges$l1 >0 & all_edges$l2 > 0, -c(15,16)]
245 
+    expanded_edges <- data.frame("edgeID" = unlist(all_edges$edgeID),
246 
+                            "entry1accession" =
247 
+                                unlist(all_edges$entry1all_accession),
248 
+                            "entry2accession" =
249 
+                                unlist(all_edges$entry2all_accession),
250 
+                            stringsAsFactors = FALSE)
251 
+
252 
+    all_edges <- all_edges[,-c(12:14)]
253 
+    all_edges$edgeID <- seq(1:nrow(all_edges))
254 
+    expanded_edges <- merge(expanded_edges, all_edges, by = "edgeID")
255 
+    for (i in 1:nrow(expanded_edges)){
256 
+        expanded_edges$entry1type[i] <-
257 
+            KEGG_mappings$entryTYPE[which(KEGG_mappings$entryID ==
258 
+                                      expanded_edges$entry1[i])][1]
259 
+        expanded_edges$entry2type[i] <-
260 
+            KEGG_mappings$entryTYPE[which(KEGG_mappings$entryID ==
261 
+                                      expanded_edges$entry2[i])][1]
262 
+        if (expanded_edges$entry1type[i] == "gene"|
263 
+            expanded_edges$entry1type[i] == "compound") {
264 
+            expanded_edges$entry1symbol[i] <-
265 
+            KEGG_mappings$entrySYMBOL[which(KEGG_mappings$entryACCESSION ==
266 
+                                        expanded_edges$entry1accession[i])][1]
267 
+            }
268 
+        else {
269 
+            expanded_edges$entry1symbol[i] <- NA
270 
+        }
271 
+        if (expanded_edges$entry2type[i] == "gene" |
272 
+            expanded_edges$entry2type[i] == "compound") {
273 
+            expanded_edges$entry2symbol[i] <-
274 
+            KEGG_mappings$entrySYMBOL[which(KEGG_mappings$entryACCESSION ==
275 
+                                        expanded_edges$entry2accession[i])][1]
276 
+        }
277 
+        else {
278 
+            expanded_edges$entry2symbol[i] <- NA
279 
+        }
280 
+    }
281 
+    expanded_edges$entry1symbol <- unlist(expanded_edges$entry1symbol)
282 
+    expanded_edges$entry2symbol <- unlist(expanded_edges$entry2symbol)
283 
+    expanded_edges$is_direct <- as.numeric(expanded_edges$is_direct)
284 
+    return(expanded_edges)
285 
+}
R/expand_KEGG_mappings.R
History View file @ 4614338
0 286 
new file mode 100644
... ... 
@@ -0,0 +1,269 @@
1 
+#' Get detailed KEGG mapping information for each map entity
2 
+#' @description Extract mapping information from KGML object and normalize
3 
+#' mappings based on multi-valued name attribute
4 
+#'
5 
+#' @param KGML_file An object of formal class KEGGPathway
6 
+#' @param convert_KEGG_IDs A logical indicator; if set to FALSE will run faster
7 
+#'  however genes and compounds will remain labeled via KEGG codes (compounds)
8 
+#'  or accession numbers (genes).  This option must be taken into account if
9 
+#'  data is being added.  For example, the genes in 'KO_data' are identified by
10 
+#'  symbols, thus it is neccessary to retain the default option to convert IDs
11 
+#'  to symbols when planning to add edge data of this type.
12 
+#'
13 
+#' @return A dataframe object with unique entry information for all [node]
14 
+#'  objects documented in the KEGG pathway.
15 
+#'         Note that if mutiple objects (i.e. genes or compounds) have the same
16 
+#'         entryID, this indicates that they share the same node [location]
17 
+#'         in the pathway.
18 
+#' @export
19 
+#' @import org.Hs.eg.db
20 
+#' @import KEGGREST
21 
+#' @import AnnotationDbi
22 
+#' @importMethodsFrom KEGGgraph edges
23 
+#' @importMethodsFrom KEGGgraph nodes
24 
+#' @examples
25 
+#' p53_KGML <- get_KGML("hsa04115")
26 
+#' p53_KEGG_mappings <-  expand_KEGG_mappings(p53_KGML, FALSE)
27 
+
28 
+expand_KEGG_mappings <-
29 
+function (KGML_file, convert_KEGG_IDs = TRUE){
30 
+    nodesN <- KEGGgraph::nodes(KGML_file)
31 
+    entryMAP<- data.frame(entry = seq(1:length(nodesN)))
32 
+    for (i in 1:nrow(entryMAP)){
33 
+        entryMAP$entryID[i] <- nodesN[[i]]@entryID
34 
+        entryMAP$entryTYPE[i] <- nodesN[[i]]@type
35 
+        entryMAP$entryIDENTIFIER[i] <- list(nodesN[[i]]@name)
36 
+        if (entryMAP$entryTYPE[i] == "group"){
37 
+            entryMAP$groupMEMBERS[i] <-
38 
+                list(nodesN[[entryMAP$entryID[i]]]@component)
39 
+            entryMAP$entryIDENTIFIER[i] <-
40 
+                list(entryMAP$entryIDENTIFIER[which(entryMAP$entryID %in%
41 
+                                            unlist(entryMAP$groupMEMBERS[i]))])
42 
+        }
43 
+        else {
44 
+            entryMAP$groupMEMBERS[i] <- NA
45 
+        }
46 
+        if (entryMAP$entryTYPE[i] == "gene" |
47 
+            entryMAP$entryTYPE[i] == "compound"|
48 
+            entryMAP$entryTYPE[i] == "group"){
49 
+                entryMAP$entryACCESSION[i]<- list(gsub(".*:", "",
50 
+                                        unlist(entryMAP$entryIDENTIFIER[i])))
51 
+        }
52 
+        else {
53 
+            entryMAP$entryACCESSION[i] <- NA
54 
+        }
55 
+        entryMAP$entryTYPE[i] <- nodesN[[i]]@type
56 
+        entryMAP$entryNAMES[i] <- nodesN[[i]]@graphics@name
57 
+        entryMAP$FGcolor[i] <- nodesN[[i]]@graphics@fgcolor
58 
+        entryMAP$BGcolor[i] <- nodesN[[i]]@graphics@bgcolor
59 
+        entryMAP$shape[i] <- nodesN[[i]]@graphics@type
60 
+        entryMAP$Xcoord[i] <- nodesN[[i]]@graphics@x
61 
+        entryMAP$Ycoord[i] <- nodesN[[i]]@graphics@y
62 
+        entryMAP$width[i] <- nodesN[[i]]@graphics@width
63 
+        entryMAP$height[i] <- nodesN[[i]]@graphics@height
64 
+        if(is.na(entryMAP$entryNAMES[i])){
65 
+            entryMAP$entryNAMES[i] <- "NoNameInKGML"
66 
+        }
67 
+    }
68 
+    entryMAP <- entryMAP[,-c(1,4)]
69 
+    entryMAP_groupings <- entryMAP[entryMAP$entryTYPE == "group",]
70 
+    entryMAP_extra <- entryMAP[entryMAP$entryTYPE == "map",]
71 
+    entryMAP_extra$entrySYMBOL <- NA
72 
+    entryMAP_dictionary <- entryMAP[entryMAP$entryTYPE == "gene" |
73 
+                                    entryMAP$entryTYPE == "compound",]
74 
+    for (i in 1:nrow(entryMAP_dictionary)){
75 
+        if (entryMAP_dictionary$entryTYPE[i] == "compound"){
76 
+            entryMAP_dictionary$entryACCESSION[i] <-
77 
+            entryMAP_dictionary$entryACCESSION[[i]][1]
78 
+        }
79 
+    }
80 
+    if(convert_KEGG_IDs){
81 
+        for (i in 1:nrow(entryMAP_dictionary)){
82 
+            if (entryMAP_dictionary$entryTYPE[i] == "compound"){
83 
+                testval <-
84 
+                    keggGet(entryMAP_dictionary$entryACCESSION[i])[[1]]$NAME
85 
+                if(!is.null(testval)){
86 
+                    entryMAP_dictionary$entryNAMES[i] <- list(testval)
87 
+                    entryMAP_dictionary$entryNAMES[i] <-
88 
+                        list(gsub(";", "",
89 
+                                unlist(entryMAP_dictionary$entryNAMES[i])))
90 
+                }
91 
+            }
92 
+        }
93 
+    }
94 
+    for (i in 1:nrow(entryMAP_dictionary)){
95 
+        l = length(unlist(entryMAP_dictionary$entryACCESSION[i]))
96 
+        entryMAP_dictionary$entryID[i] <-
97 
+            list(rep(entryMAP_dictionary$entryID[i], l))
98 
+        entryMAP_dictionary$entryTYPE[i] <-
99 
+            list(rep(entryMAP_dictionary$entryTYPE[i], l))
100 
+    }
101 
+    emd_temp <- data.frame(cbind(unlist(entryMAP_dictionary$entryID),
102 
+                                unlist(entryMAP_dictionary$entryTYPE),
103 
+                                unlist(entryMAP_dictionary$entryACCESSION)),
104 
+                                stringsAsFactors = FALSE)
105 
+    names(emd_temp) <- names(entryMAP[c(1,2,4)])
106 
+    for (i in 1:nrow(emd_temp)){
107 
+        if (emd_temp$entryTYPE[i] == "gene"){
108 
+            if (convert_KEGG_IDs){
109 
+                emd_temp$entrySYMBOL[i] <-
110 
+                suppressMessages(as.character(AnnotationDbi::select(
111 
+                org.Hs.eg.db::org.Hs.eg.db,keys = emd_temp$entryACCESSION[i],
112 
+                columns=c("SYMBOL"),keytype="ENTREZID")[2]))
113 
+            }
114 
+            else {
115 
+                emd_temp$entrySYMBOL[i] <- emd_temp$entryACCESSION[i]
116 
+            }
117 
+        }
118 
+        else if (emd_temp$entryTYPE[i] == "compound"){
119 
+            emd_temp$entrySYMBOL[i] <- unlist(
120 
+                entryMAP_dictionary$entryNAMES[
121 
+                    entryMAP_dictionary$entryACCESSION ==
122 
+                    emd_temp$entryACCESSION[i]])[1]
123 
+        }
124 
+        else {
125 
+            emd_temp$entrySYMBOL[i] <- NA
126 
+        }
127 
+    }
128 
+    for (i in 1:nrow(emd_temp)){
129 
+        if (gsub("[[:digit:]]","",emd_temp$entryACCESSION[i]) == "G" &
130 
+            is.na(emd_temp$entrySYMBOL[i])){
131 
+            emd_temp$entrySYMBOL[i] <- emd_temp$entryACCESSION[i]
132 
+        }
133 
+    }
134 
+    emd_temp$groupMEMBERS <- NA
135 
+    for(i in 1:nrow(entryMAP_dictionary)){
136 
+        entryMAP_dictionary$entryID[i] <-
137 
+            unlist(entryMAP_dictionary$entryID[i])[1]
138 
+        entryMAP_dictionary$entryTYPE[i] <-
139 
+            unlist(entryMAP_dictionary$entryTYPE[i])[1]
140 
+        if(entryMAP_dictionary$entryTYPE[i] == "compound"){
141 
+            entryMAP_dictionary$entryNAMES[i] <-
142 
+                toString(unlist(entryMAP_dictionary$entryNAMES[[i]]))
143 
+        }
144 
+    }
145 
+    entryMAP_dictionary <- entryMAP_dictionary[,-c(2:4)]
146 
+    entryMAP_dictionary <- merge(emd_temp, entryMAP_dictionary, by = "entryID")
147 
+    if (nrow(entryMAP_groupings) > 0){
148 
+        for(i in 1:nrow(entryMAP_groupings)){
149 
+            entryMAP_groupings$entrySYMBOL[i] <-
150 
+                list(entryMAP_dictionary$entrySYMBOL[match(unlist(
151 
+                    entryMAP_groupings$entryACCESSION[i]),
152 
+                    entryMAP_dictionary$entryACCESSION)])
153 
+        }
154 
+        entryMAP_dictionary <-
155 
+            rbind(entryMAP_extra, entryMAP_dictionary, entryMAP_groupings)
156 
+        no_groups <- FALSE
157 
+    }
158 
+    if (nrow(entryMAP_groupings) == 0){
159 
+        entryMAP_dictionary <- rbind(entryMAP_extra, entryMAP_dictionary)
160 
+        entryMAP_dictionary$groupMEMBERS <- NA
161 
+        entryMAP_dictionary$groupID <- NA
162 
+        no_groups = TRUE
163 
+    }
164 
+
165 
+    entryMAP_dictionary <-
166 
+        entryMAP_dictionary[order(as.double(entryMAP_dictionary$entryID)),]
167 
+    rownames(entryMAP_dictionary) <- seq(1:nrow(entryMAP_dictionary))
168 
+    entryMAP_dictionary$entryNAMES <- gsub("...", "",
169 
+                                            entryMAP_dictionary$entryNAMES,
170 
+                                            fixed = TRUE)
171 
+    for (i in 1:nrow(entryMAP_dictionary)){
172 
+        if (entryMAP_dictionary$entryTYPE[i] =="gene"){
173 
+            entryMAP_dictionary$LABEL[i] <- strsplit(as.character(
174 
+                entryMAP_dictionary$entryNAMES[[i]]), ",")[[1]][1]
175 
+        }
176 
+        else if (entryMAP_dictionary$entryTYPE[i] == "compound"){
177 
+            entryMAP_dictionary$LABEL[i] <- entryMAP_dictionary$entrySYMBOL[i]
178 
+        }
179 
+        else {
180 
+            entryMAP_dictionary$LABEL[i] = entryMAP_dictionary$entryNAMES[i]
181 
+        }
182 
+    }
183 
+    for (i in 1:nrow(entryMAP_dictionary)){
184 
+        if (entryMAP_dictionary$entryTYPE[i] == "group"){
185 
+            entryMAP_dictionary$entryNAMES[i] <-
186 
+                paste0(paste(unique(entryMAP_dictionary$LABEL[which(
187 
+                entryMAP_dictionary$entryID %in%
188 
+                unlist(entryMAP_dictionary$groupMEMBERS[i]))]),collapse = ":"),
189 
+                " Complex")
190 
+            entryMAP_dictionary$LABEL[i] <- entryMAP_dictionary$entryNAMES[i]
191 
+        }
192 
+    }
193 
+    if (!no_groups){
194 
+        for (i in 1:nrow(entryMAP_groupings)){
195 
+            l <- length(unlist(entryMAP_groupings$groupMEMBERS[i]))
196 
+            entryMAP_groupings$entryID[i] <-
197 
+                list(rep(entryMAP_groupings$entryID[i], l))
198 
+        }
199 
+        group_mapper <- data.frame("groupID" =
200 
+                                    unlist(entryMAP_groupings$entryID),
201 
+                            "entryID" =
202 
+                                unlist(entryMAP_groupings$groupMEMBERS),
203 
+                            stringsAsFactors = FALSE)
204 
+        for (i in 1:nrow(entryMAP_dictionary)){
205 
+            if (entryMAP_dictionary$entryID[i] %in% group_mapper$entryID){
206 
+                entryMAP_dictionary$groupID[i] <-
207 
+                    group_mapper$groupID[match(entryMAP_dictionary$entryID[i],
208 
+                                        group_mapper$entryID)]
209 
+            }
210 
+            else {
211 
+                entryMAP_dictionary$groupID[i] <- NA
212 
+            }
213 
+        }
214 
+    }
215 
+
216 
+    num_edges <- length(KGML_file@edges)
217 
+    if (num_edges > 0){
218 
+        map_edge_data<- KEGGgraph::edges(KGML_file)
219 
+        edges<- data.frame(edgeID = seq(1:length(map_edge_data )))
220 
+        for (i in 1:nrow(edges)){
221 
+            edges$entry1[i] <- as.character(map_edge_data[[i]]@entry1ID)
222 
+            edges$entry2[i] <- as.character(map_edge_data[[i]]@entry2ID)
223 
+        }
224 
+        for (i in 1:nrow(entryMAP_dictionary)){
225 
+            if (entryMAP_dictionary$entryID[i] %in% edges$entry1 |
226 
+                entryMAP_dictionary$entryID[i] %in% edges$entry2){
227 
+                    entryMAP_dictionary$in_relationship[i] = 1
228 
+            }
229 
+            else if (entryMAP_dictionary$groupID[i] %in% edges$entry1 |
230 
+                    entryMAP_dictionary$groupID[i] %in% edges$entry2){
231 
+                    entryMAP_dictionary$in_relationship[i] = 1
232 
+            }
233 
+            else {
234 
+                entryMAP_dictionary$in_relationship[i] = 0
235 
+            }
236 
+        }
237 
+    }
238 
+    if (num_edges == 0){
239 
+      entryMAP_dictionary$in_relationship = 0
240 
+    }
241 
+    for (i in 1:nrow(entryMAP_dictionary)){
242 
+        if (is.na(entryMAP_dictionary$entrySYMBOL[i])){
243 
+            entryMAP_dictionary$entrySYMBOL[i] <- entryMAP_dictionary$LABEL[i]
244 
+        }
245 
+    }
246 
+    map_nodes <- entryMAP_dictionary$LABEL[entryMAP_dictionary$entryTYPE=="map"]
247 
+    j = 0
248 
+    for (i in 1:length(map_nodes)){
249 
+        if (substring(map_nodes[i],1,5) == "TITLE"){
250 
+            j = j+1
251 
+        }
252 
+    }
253 
+    if (j == 0){
254 
+        title <- KGML_file@pathwayInfo@title
255 
+        min_Y <- min(entryMAP_dictionary$Ycoord)
256 
+        min_X <- min(entryMAP_dictionary$Xcoord)+100
257 
+        title_node <- data.frame("entryID" = 0, "entryTYPE" = "map",
258 
+                                "groupMEMBERS" = NA, "entryACCESSION" = NA,
259 
+                                "entryNAMES" = title,
260 
+                                "FGcolor" = "#000000", "BGcolor" = "#FFFFFF",
261 
+                                "shape" = "rectangle", "Xcoord" = min_X,
262 
+                                "Ycoord"= min_Y, "height" = 25, "width" = 220,
263 
+                                "entrySYMBOL"= title, "groupID"=NA,
264 
+                                "LABEL"=paste0("TITLE:",title),
265 
+                                "in_relationship" = 0)
266 
+        entryMAP_dictionary <- rbind(entryMAP_dictionary, title_node)
267 
+    }
268 
+    return(entryMAP_dictionary)
269 
+}
0 270 
\ No newline at end of file
R/from_cyREST.R
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1 271 
new file mode 100644
... ... 
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1 
+#' cyREST utility functions
2 
+#' @description A subset of the R utility functions available from/defined
3 
+#'  by cyREST.  The function mapAttributes is called from within toCytoscape
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+#'  which, in turn, is called from within cyto_vis.
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+#' @export
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+#' @import methods
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+#' @importFrom igraph E edge_attr graph.attributes V vertex.attributes
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+#'  list.vertex.attributes get.edgelist ecount edge.attributes
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+#'  list.edge.attributes
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+#' @param attr.names Attribute names of an igraph object
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+#' @param all.attr The attribute value if an igraph object
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+#' @param i The index for a given igraph object
13 
+#' @param igraphobj A graph object compatible for use with the package igraph