feat(indra): Fetch networks from indra cogex and visualize with cytos…

…cape

NAMESPACE

@@ -36,6 +36,7 @@ export(dataProcessPlots)
 export(designSampleSize)
 export(designSampleSizePlots)
 export(extractSDRF)
+export(fetchIndraData)
 export(getProcessed)
 export(getSamplesInfo)
 export(getSelectedProteins)
@@ -46,6 +47,7 @@ export(modelBasedQCPlots)
 export(quantification)
 export(savePlot)
 export(theme_msstats)
+export(visualizeNetworks)
 import(data.table)
 import(ggplot2)
 import(limma)
@@ -57,12 +59,17 @@ importFrom(MSstatsConvert,MSstatsImport)
 importFrom(MSstatsConvert,MSstatsLogsSettings)
 importFrom(MSstatsConvert,MSstatsMakeAnnotation)
 importFrom(MSstatsConvert,MSstatsPreprocess)
+importFrom(RCy3,createNetworkFromDataFrames)
+importFrom(RCy3,createVisualStyle)
+importFrom(RCy3,mapVisualProperty)
+importFrom(RCy3,setVisualStyle)
 importFrom(Rcpp,sourceCpp)
 importFrom(data.table,as.data.table)
 importFrom(data.table,melt)
 importFrom(data.table,rbindlist)
 importFrom(data.table,setDT)
 importFrom(data.table,uniqueN)
+importFrom(dplyr,filter)
 importFrom(ggrepel,geom_text_repel)
 importFrom(gplots,heatmap.2)
 importFrom(grDevices,dev.off)
@@ -79,6 +86,10 @@ importFrom(graphics,title)
 importFrom(htmltools,div)
 importFrom(htmltools,save_html)
 importFrom(htmltools,tagList)
+importFrom(httr,POST)
+importFrom(httr,add_headers)
+importFrom(httr,content)
+importFrom(jsonlite,toJSON)
 importFrom(limma,squeezeVar)
 importFrom(lme4,lmer)
 importFrom(marray,maPalette)
@@ -94,6 +105,9 @@ importFrom(plotly,plot_ly)
 importFrom(plotly,style)
 importFrom(plotly,subplot)
 importFrom(preprocessCore,normalize.quantiles)
+importFrom(r2r,hashmap)
+importFrom(r2r,keys)
+importFrom(r2r,query)
 importFrom(stats,dist)
 importFrom(stats,fitted)
 importFrom(stats,formula)

R/networkPlots.R

@@ -0,0 +1,98 @@
+
+#' Fetch data on a set of proteins from INDRA
+#' 
+#' @param input groupComparison comparisionResult table
+#' @param pvalue_cutoff p-value cutoff for filtering
+#' @param stmt_types types of statements to filter, default is "Complex"
+#' @importFrom jsonlite toJSON
+#' @importFrom httr POST add_headers content
+#' @importFrom r2r hashmap query keys
+#' @importFrom dplyr filter
+#' 
+#' @export
+#' 
+#' @noRd
+#'
+#'   
+fetchIndraData = function(input, pvalue_cutoff = 0.05, stmt_types = c("Complex")) {
+    input = filter(input, adj.pvalue < pvalue_cutoff)
+    input = filter(input, is.na(issue))
+    hgnc_ids = input$HgncId
+    uniprot_ids = input$Protein
+    gene_id_map = hashmap()
+    gene_id_map[input$HgncId] = input$HgncName
+    url = "https://discovery.indra.bio/api/indra_subnetwork_relations"
+    groundings = lapply(hgnc_ids, function(x) list("HGNC", x))
+    groundings = list(nodes = groundings)
+    json_body = jsonlite::toJSON(groundings, auto_unbox = TRUE)
+    res = POST(url, body = json_body, add_headers("Content-Type" = "application/json"), encode = "raw")
+    output = content(res)
+    output = Filter(function(x) x$data$stmt_type %in% stmt_types, output)
+
+    edge_data = hashmap()
+    for (edge in output) {
+        key = paste(edge$source_id, edge$target_id, edge$data$stmt_type, sep="_")
+        if (key %in% keys(edge_data)) {
+            edge_data[[key]]$data$evidence_count = edge_data[[key]]$data$evidence_count + edge$data$evidence_count
+        } else {
+            edge_data[[key]] = edge
+        }
+    }
+    evidenceList = sapply(keys(edge_data), function(x) 
+        paste("https://db.indra.bio/statements/from_agents?subject=", 
+              query(gene_id_map, query(edge_data, x)$source_id), "&object=", 
+              query(gene_id_map, query(edge_data, x)$target_id), "&type=",
+              query(edge_data, x)$data$stmt_type, "&format=html", sep=""))
+
+
+    nodes = data.frame(id=hgnc_ids,
+                       uniprot_id=uniprot_ids,
+                       logFC=input$log2FC, 
+                       pvalue=input$adj.pvalue,
+                       stringsAsFactors=FALSE)
+    edges = data.frame(source=sapply(keys(edge_data), function(x) query(edge_data, x)$source_id),
+                       target=sapply(keys(edge_data), function(x) query(edge_data, x)$target_id),
+                       interaction=sapply(keys(edge_data), function(x) query(edge_data, x)$data$stmt_type), 
+                       evidenceCount=sapply(keys(edge_data), function(x) query(edge_data, x)$data$evidence_count),
+                       evidenceLink=evidenceList,
+                       stringsAsFactors=FALSE)
+
+    return(list(nodes=nodes, edges=edges))
+}
+
+#' Create visualization of networks in cytoscape
+#' 
+#' @param nodes dataframe of nodes
+#' @param edges dataframe of edges
+#' @importFrom RCy3 createNetworkFromDataFrames mapVisualProperty createVisualStyle setVisualStyle
+#' 
+#' @export
+#' 
+#' @noRd
+#'
+#'               
+visualizeNetworks = function(nodes, edges) {
+  network_id = createNetworkFromDataFrames(nodes, edges, title="my first network", collection="DataFrame Example")
+  arrowShapes = mapVisualProperty(
+      'Edge Target Arrow Shape','interaction',
+      'd',
+      c("Complex", "Activation", "Inhibition"),
+      c("Arrow","Arrow","Arrow")
+  )
+  nodeLabels = mapVisualProperty('Node Label','uniprot_id','p')
+  edgeWidth = mapVisualProperty('Edge Width','evidenceCount','p')
+  createVisualStyle("Y",
+                    list(
+                        NODE_FILL_COLOR="lightblue",
+                        NODE_SHAPE="ROUNDRECT",
+                        NODE_SIZE=50,
+                        NODE_LABEL_FONT_SIZE=6,
+                        NODE_LABEL_POSITION="center"), 
+                    list(
+                        nodeLabels, 
+                        edgeWidth,
+                        arrowShapes
+                    ))
+  setVisualStyle("Y")
+
+}