Merge branch 'f-top5pct-overexpressed'

-- converts up_ and down_ genes outlier analysis output files to blobs2
-- adds top5% overexpressed outlier analysis file

config/ekephart/run.sh

@@ -0,0 +1,4 @@
+export MONGO_URL="mongodb://localhost:27017/MedBook"
+export MEDBOOK_FILESTORE=/tmp/filestore
+
+meteor --port 3003 --settings ../config/ekephart/settings.json

config/ekephart/settings.json

@@ -0,0 +1,12 @@
+{
+  "sh": "/bin/sh",
+  "rscript": "Rscript",
+  "limma_path": "/Users/ekephart/code/jobrunner/external-tools/limma/limma_ng.R",
+  "outlier_analysis": "/Users/ekephart/code/jobrunner/external-tools/OutlierAnalysis/outlier-analysis.sh",
+  "calculate_outlier_genes": "/Users/ekephart/code/jobrunner/external-tools/OutlierAnalysis/calculate_outlier_genes.R",
+  "genomic_expression_export": "/Users/ekephart/code/jobrunner/external-tools/exporters/genomic_expression_export.py",
+  "gene_set_collection_export": "/Users/ekephart/code/jobrunner/external-tools/exporters/gene_set_collection_export.py",
+  "limma_phenotype_export": "/Users/ekephart/code/jobrunner/external-tools/exporters/limma_phenotype_export.py",
+  "gsea_path": "/Users/ekephart/code/jobrunner/external-tools/gsea/rgGSEA.py",
+  "gsea_jar_path": "/Users/ekephart/code/jobrunner/external-tools/gsea/gsea2-2.2.2.jar"
+}

webapp/server/classes/UpDownGenes.js

@@ -129,17 +129,37 @@ UpDownGenes.prototype.run = function () {
       // calculate the paths for the output files
       upPath = path.join(workDir, "up_outlier_genes")
       downPath = path.join(workDir, "down_outlier_genes")
+      top5Path = path.join(workDir, "top_5_percent_most_highly_expressed_genes.tsv")
 
-      // insert blobs into mongo
-      var output = {
-        up_blob_id: Blobs.insert(upPath)._id,
-        down_blob_id: Blobs.insert(downPath)._id,
+
+      // Save output files as Blobs2 "synchronously" with wrapAsync
+
+      var output = {};
+      var associated_job_object = {
+        collection_name: "Jobs",
+        mongo_id: self.job._id,
       };
+      var createBlob2Sync = Meteor.wrapAsync(Blobs2.create);
+
+      try{
+        var upGenesBlob = createBlob2Sync(upPath, associated_job_object, {});
+        var downGenesBlob = createBlob2Sync(downPath, associated_job_object, {});
+        var top5blob = createBlob2Sync(top5Path, associated_job_object, {});
+        output["up_blob_id"] = upGenesBlob._id;
+        output["down_blob_id"] = downGenesBlob._id;
+        output["top5percent_blob_id"] = top5blob._id;
+      }catch(error){
+        // Log the error and throw it again to properly fail the outlier analysis job
+        console.log("Error storing output files for Outlier Analysis:", error);
+        throw(error);
+      }
+
 
       // parse strings
       _.each([
-        { name: "up_genes", fileString: fs.readFileSync(upPath, "utf8") },
-        { name: "down_genes", fileString: fs.readFileSync(downPath, "utf8") },
+        { name: "up_genes", fileString: fs.readFileSync(upGenesBlob.getFilePath(), "utf8") },
+        { name: "down_genes", fileString: fs.readFileSync(downGenesBlob.getFilePath(), "utf8") },
+        { name: "top5percent_genes", fileString: fs.readFileSync(top5blob.getFilePath(), "utf8") },
       ], function (outlier) {
         var lineArray = outlier.fileString.split("\n");
         var filteredLines = _.filter(lineArray, function (line) {
@@ -148,19 +168,31 @@ UpDownGenes.prototype.run = function () {
 
         // loop for each line
         output[outlier.name] = _.map(filteredLines, function (line) {
-          var tabSplit = line.split(" ");
-          return {
-            gene_label: tabSplit[0],
-            background_median: parseFloat(tabSplit[1]),
-            sample_value: parseFloat(tabSplit[2]),
-          };
+          // Populate the found genes.
+          // The top5percent overexpressed file has a different format from the
+          // other files so split its columns separately.
+          if(outlier.name == "top5percent_genes"){
+            var tabSplit = line.split("\t");
+            return {
+              gene_label: tabSplit[0],
+              sample_value: parseFloat(tabSplit[1]),
+              // no background_median
+            }
+          }else{
+            var tabSplit = line.split(" ");
+            return {
+              gene_label: tabSplit[0],
+              background_median: parseFloat(tabSplit[1]),
+              sample_value: parseFloat(tabSplit[2]),
+            };
+          }
         });
       });
 
       deferred.resolve(output);
     }, deferred.reject))
-    // NOTE: Meteor.bindEnvironment returns immidiately, meaning we can't
-    // quite use the nice promise syntax of chainging .thens
+    // NOTE: Meteor.bindEnvironment returns immediately, meaning we can't
+    // quite use the nice promise syntax of chaining .thens
     .catch(deferred.reject);
   return deferred.promise;
 };