Merge pull request #232 from DannyArends/testing

Updates to the CTL analysis

4 files changed, 288 insertions, 8 deletions

diff --git a/wqflask/wqflask/ctl/ctl_analysis.py b/wqflask/wqflask/ctl/ctl_analysis.py
index 7a42b2f8..3d2d7a37 100644
--- a/wqflask/wqflask/ctl/ctl_analysis.py
+++ b/wqflask/wqflask/ctl/ctl_analysis.py
@@ -6,6 +6,8 @@ import scipy as sp                            # SciPy
 import rpy2.robjects as ro                    # R Objects
 import rpy2.rinterface as ri
 
+import simplejson as json
+
 from base.webqtlConfig import GENERATED_IMAGE_DIR
 from utility import webqtlUtil                # Random number for the image
 from utility import genofile_parser           # genofile_parser
@@ -73,8 +75,30 @@ class CTL(object):
         self.r_CTLnetwork         = ro.r["CTLnetwork"]                     # Map the CTLnetwork function
         self.r_CTLprofiles        = ro.r["CTLprofiles"]                    # Map the CTLprofiles function
         self.r_plotCTLobject      = ro.r["plot.CTLobject"]                 # Map the CTLsignificant function
+        self.nodes_list = []
+        self.edges_list = []
         print("Obtained pointers to CTL functions")
 
+    def addNode(self, gt):
+        node_dict = { 'data' : {'id' : str(gt.name) + ":" + str(gt.dataset.name),
+                                'sid' : str(gt.name), 
+                                'dataset' : str(gt.dataset.name),
+                                'label' : gt.name,
+                                'symbol' : gt.symbol,
+                                'geneid' : gt.geneid,
+                                'omim' : gt.omim } }
+        self.nodes_list.append(node_dict)
+
+    def addEdge(self, gtS, gtT, significant, x):
+        edge_data = {'id' : str(gtS.symbol) + '_' + significant[1][x] + '_' + str(gtT.symbol),
+                     'source' : str(gtS.name) + ":" + str(gtS.dataset.name),
+                     'target' : str(gtT.name) + ":" + str(gtT.dataset.name),
+                     'lod' : significant[3][x],
+                     'color' : "#ff0000",
+                     'width' : significant[3][x] }
+        edge_dict = { 'data' : edge_data }
+        self.edges_list.append(edge_dict)
+
     def run_analysis(self, requestform):
         print("Starting CTL analysis on dataset")
         self.trait_db_list = [trait.strip() for trait in requestform['trait_list'].split(',')]
@@ -99,7 +123,7 @@ class CTL(object):
         genofilelocation = locate(dataset.group.name + ".geno", "genotype")
         parser = genofile_parser.ConvertGenoFile(genofilelocation)
         parser.process_csv()
-
+        print(dataset.group)
         # Create a genotype matrix
         individuals = parser.individuals
         markers = []
@@ -129,9 +153,11 @@ class CTL(object):
 
         rPheno = r_t(ro.r.matrix(r_as_numeric(r_unlist(traits)), nrow=len(self.trait_db_list), ncol=len(individuals), dimnames = r_list(self.trait_db_list, individuals), byrow=True))
 
+        print(rPheno)
+
         # Use a data frame to store the objects
-        rPheno = r_data_frame(rPheno)
-        rGeno = r_data_frame(rGeno)
+        rPheno = r_data_frame(rPheno, check_names = False)
+        rGeno = r_data_frame(rGeno, check_names = False)
 
         # Debug: Print the genotype and phenotype files to disk
         #r_write_table(rGeno, "~/outputGN/geno.csv")
@@ -156,7 +182,7 @@ class CTL(object):
         self.r_lineplot(res, significance = significance)
         r_dev_off()
 
-        n = 2
+        n = 2                                                 # We start from 2, since R starts from 1 :)
         for trait in self.trait_db_list:
           # Create the QTL like CTL plots
           self.results['imgurl' + str(n)] = webqtlUtil.genRandStr("CTL_") + ".png"
@@ -169,6 +195,24 @@ class CTL(object):
         # Flush any output from R
         sys.stdout.flush()
 
+        # Create the interactive graph for cytoscape visualization (Nodes and Edges)
+        print(type(significant))
+        if not type(significant) == ri.RNULLType:
+          for x in range(len(significant[0])):
+            print(significant[0][x], significant[1][x], significant[2][x])            # Debug to console
+            tsS = significant[0][x].split(':')                                        # Source
+            tsT = significant[2][x].split(':')                                        # Target
+            gtS = TRAIT.GeneralTrait(name = tsS[0], dataset_name = tsS[1])            # Retrieve Source info from the DB
+            gtT = TRAIT.GeneralTrait(name = tsT[0], dataset_name = tsT[1])            # Retrieve Target info from the DB
+            self.addNode(gtS)
+            self.addNode(gtT)
+            self.addEdge(gtS, gtT, significant, x)
+
+            significant[0][x] = gtS.symbol + " (" + gtS.name + ")"                    # Update the trait name for the displayed table
+            significant[2][x] = gtT.symbol + " (" + gtT.name + ")"                    # Update the trait name for the displayed table
+
+        self.elements = json.dumps(self.nodes_list + self.edges_list)
+
     def loadImage(self, path, name):
         print("pre-loading imgage results:", self.results[path])
         imgfile = open(self.results[path], 'rb')
@@ -188,6 +232,7 @@ class CTL(object):
         print("Processing CTL output")
         template_vars = {}
         template_vars["results"] = self.results
+        template_vars["elements"] = self.elements
         self.render_image(self.results)
         sys.stdout.flush()
         return(dict(template_vars))
diff --git a/wqflask/wqflask/static/new/javascript/ctl_graph.js b/wqflask/wqflask/static/new/javascript/ctl_graph.js
new file mode 100644
index 00000000..94bd7e9d
--- /dev/null
+++ b/wqflask/wqflask/static/new/javascript/ctl_graph.js
@@ -0,0 +1,199 @@
+window.onload=function() {
+    // id of Cytoscape Web container div
+    //var div_id = "cytoscapeweb";
+
+    var cy = cytoscape({
+      container: $('#cytoscapeweb'), // container to render in
+
+      elements: elements_list,
+
+      style: [ // the stylesheet for the graph
+          {    
+            selector: 'node',
+            style: {
+              'background-color': '#666',
+              'label': 'data(symbol)',
+              'font-size': 10
+            }
+          },
+
+          {
+            selector: 'edge',
+            style: {
+              'width': 'data(width)',
+              'line-color': 'data(color)',
+              'target-arrow-color': '#ccc',
+              'target-arrow-shape': 'none',
+              'font-size': 8,
+              'curve-style': 'bezier'
+            }
+          }
+      ],
+      
+      zoom: 12,
+      layout: { name: 'circle',
+                fit: true, // whether to fit the viewport to the graph
+                padding: 30 // the padding on fit
+                //idealEdgeLength: function( edge ){ return edge.data['correlation']*10; },                
+              }, 
+
+      
+      zoomingEnabled: true,
+      userZoomingEnabled: true,
+      panningEnabled: true,
+      userPanningEnabled: true,
+      boxSelectionEnabled: false,
+      selectionType: 'single',
+
+      // rendering options:
+      styleEnabled: true
+    });
+
+    var eles = cy.$() // var containing all elements, so elements can be restored after being removed
+    
+    var defaults = {
+      zoomFactor: 0.05, // zoom factor per zoom tick
+      zoomDelay: 45, // how many ms between zoom ticks
+      minZoom: 0.1, // min zoom level
+      maxZoom: 10, // max zoom level
+      fitPadding: 30, // padding when fitting
+      panSpeed: 10, // how many ms in between pan ticks
+      panDistance: 10, // max pan distance per tick
+      panDragAreaSize: 75, // the length of the pan drag box in which the vector for panning is calculated (bigger = finer control of pan speed and direction)
+      panMinPercentSpeed: 0.25, // the slowest speed we can pan by (as a percent of panSpeed)
+      panInactiveArea: 8, // radius of inactive area in pan drag box
+      panIndicatorMinOpacity: 0.5, // min opacity of pan indicator (the draggable nib); scales from this to 1.0
+      zoomOnly: false, // a minimal version of the ui only with zooming (useful on systems with bad mousewheel resolution)
+      fitSelector: undefined, // selector of elements to fit
+      animateOnFit: function(){ // whether to animate on fit
+        return false;
+      },
+      fitAnimationDuration: 1000, // duration of animation on fit
+
+      // icon class names
+      sliderHandleIcon: 'fa fa-minus',
+      zoomInIcon: 'fa fa-plus',
+      zoomOutIcon: 'fa fa-minus',
+      resetIcon: 'fa fa-expand'
+    };
+
+    cy.panzoom( defaults );
+    
+    function create_qtips(cy){
+        cy.nodes().qtip({
+                            content: function(){
+                                gn_link = '<b>'+'<a href="http://gn2.genenetwork.org/show_trait?trait_id=' + this.data().sid + '&dataset=' + this.data().dataset + '" >'+this.data().id +'</a>'+'</b><br>'
+                                ncbi_link = '<a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=gene&cmd=Retrieve&dopt=Graphics&list_uids=' + this.data().geneid + '" >NCBI<a>'+'<br>' 
+                                omim_link = '<a href="http://www.ncbi.nlm.nih.gov/omim/' + this.data().omim + '" >OMIM<a>'+'<br>' 
+                                qtip_content = gn_link + ncbi_link + omim_link
+                                return qtip_content
+                                //return '<b>'+'<a href="http://gn2.genenetwork.org/show_trait?trait_id=' + this.data().id + '&dataset=' + this.data().dataset + '" >'+this.data().id +'<a>'+'</b>' 
+                            },
+                            // content: {
+                                // title: '<b>'+'<a href="http://gn2.genenetwork.org/show_trait?trait_id=' + this.target() + '&dataset=' + this.dataset() + '" >'+this.target() +'<a>'+'</b>',
+                                // text: this.target,
+                                // button: true
+                            // },
+                            position: {
+                                my: 'top center',
+                                at: 'bottom center'
+                            },
+                            style: {
+                                classes: 'qtip-bootstrap',
+                                tip: {
+                                    width: 16,
+                                    height: 8
+                                }
+                            }
+                        });
+                        
+        cy.edges().qtip({
+                            content: function(){
+                                edge_ID = '<b>Edge: ' + this.data().id + '</b><br>'
+                                lod_score = 'LOD: ' + this.data().lod + '<br>'
+                                return edge_ID + lod_score
+                            },
+                            position: {
+                                my: 'top center',
+                                at: 'bottom center'
+                            },
+                            style: {
+                                classes: 'qtip-bootstrap',
+                                tip: {
+                                    width: 16,
+                                    height: 8
+                                }
+                            }
+                        });    
+    }
+    
+    create_qtips(cy)
+    
+    $('#slide').change(function() {
+        eles.restore()
+        
+        console.log(eles)
+        
+        // nodes_to_restore = eles.filter("node[max_corr >= " + $(this).val() + "], edge[correlation >= " + $(this).val() + "][correlation <= -" + $(this).val() + "]")
+        // nodes_to_restore.restore()
+        
+        // edges_to_restore = eles.filter("edge[correlation >= " + $(this).val() + "][correlation <= -" + $(this).val() + "]")
+        // edges_to_restore.restore()
+        
+        //cy.$("node[max_corr >= " + $(this).val() + "]").restore();
+        //cy.$("edge[correlation >= " + $(this).val() + "][correlation <= -" + $(this).val() + "]").restore();
+        
+        cy.$("node[max_corr < " + $(this).val() + "]").remove(); 
+        cy.$("edge[correlation < " + $(this).val() + "][correlation > -" + $(this).val() + "]").remove();
+
+        cy.layout({ name: $('select[name=layout_select]').val(),
+                    fit: true, // whether to fit the viewport to the graph
+                    padding: 25 // the padding on fit              
+                  });
+        
+    });
+    
+    $('#reset_graph').click(function() {
+        eles.restore() 
+        $('#slide').val(0)
+        cy.layout({ name: $('select[name=layout_select]').val(),
+                    fit: true, // whether to fit the viewport to the graph
+                    padding: 25 // the padding on fit              
+                  });
+    });
+    
+    $('select[name=focus_select]').change(function() {
+        focus_trait = $(this).val()
+
+        eles.restore()
+        cy.$('edge[source != "' + focus_trait + '"][target != "' + focus_trait + '"]').remove()
+
+        cy.layout({ name: $('select[name=layout_select]').val(),
+                    fit: true, // whether to fit the viewport to the graph
+                    padding: 25 // the padding on fit              
+                  });
+    });
+    
+    $('select[name=layout_select]').change(function() {
+        layout_type = $(this).val()
+        console.log("LAYOUT:", layout_type)
+        cy.layout({ name: layout_type,
+                    fit: true, // whether to fit the viewport to the graph
+                    padding: 25 // the padding on fit              
+                  });
+    });
+    
+    $("a#image_link").click(function(e) {
+      var pngData = cy.png();
+
+      $(this).attr('href', pngData);
+      $(this).attr('download', 'network_graph.png');
+      
+      console.log("TESTING:", image_link)
+      
+    });
+
+    
+};
+
+
diff --git a/wqflask/wqflask/templates/ctl_results.html b/wqflask/wqflask/templates/ctl_results.html
index 00ccecb6..969ca18a 100644
--- a/wqflask/wqflask/templates/ctl_results.html
+++ b/wqflask/wqflask/templates/ctl_results.html
@@ -1,17 +1,30 @@
 {% extends "base.html" %}
+{% block css %}
+    <link rel="stylesheet" type="text/css" href="/static/new/css/network_graph.css" />
+    <link rel="stylesheet" type="text/css" href="/static/packages/cytoscape/css/cytoscape.js-panzoom.css" />
+    <link rel="stylesheet" type="text/css" href="http://cdnjs.cloudflare.com/ajax/libs/qtip2/2.2.0/jquery.qtip.css">
+    <style>
+        /* The Cytoscape Web container must have its dimensions set. */
+        html, body { height: 100%; width: 100%; padding: 0; margin: 0; }
+        #cytoscapeweb { width: 70%; height: 70%; }
+    </style>
+{% endblock %}
+
 {% block title %}CTL results{% endblock %}
 
 {% block content %} <!-- Start of body -->
 <div class="container">
   <h1>CTL Results</h1>
   {{(request.form['trait_list'].split(',')|length)}} phenotypes as input<br>
-  <h3>Network Figure</h3>
+
+  <!--
   <a href="/tmp/{{ results['imgurl1'] }}">
       <img alt="Embedded Image" src="data:image/png;base64,
       {% for elem in results['imgdata1'] -%}
       {% print("%c"|format(elem)) %}
       {%- endfor %}
-      " /></a>
+      " /></a> -->
+  
   <h3>CTL/QTL Plots for individual traits</h3>
   {% for r in range(2, (request.form['trait_list'].split(',')|length +1)) %}
   <a href="/tmp/{{ results['imgurl' + r|string] }}">
@@ -39,9 +52,26 @@
     </tr>
   {% endfor %}
   </table>
+  <h3>Network Figure</h3>
+  <div id="cytoscapeweb" class="col-xs-9" style="min-height:700px !important;"></div>
+</div>
+{% endblock %}
 
+{% block js %}
 
+    <script>
+        elements_list = {{ elements | safe }}
+    </script>
 
+    <script language="javascript" type="text/javascript" src="/static/new/packages/DataTables/js/jquery.js"></script>
+    <script language="javascript" type="text/javascript" src="http://cdnjs.cloudflare.com/ajax/libs/qtip2/2.2.0/jquery.qtip.js"></script>
+    <script language="javascript" type="text/javascript" src="/static/packages/underscore/underscore-min.js"></script>
+    <script language="javascript" type="text/javascript" src="/static/packages/cytoscape/js/min/cytoscape.min.js"></script>
+    <script language="javascript" type="text/javascript" src="/static/packages/cytoscape/js/min/AC_OETags.min.js"></script>
+    <script language="javascript" type="text/javascript" src="/static/packages/cytoscape/js/min/json2.min.js"></script>
+    <script language="javascript" type="text/javascript" src="/static/packages/cytoscape/js/src/cytoscape-panzoom.js"></script>
+    <script language="javascript" type="text/javascript" src="/static/packages/cytoscape/js/src/cytoscape-qtip.js"></script>
 
-</div>
+    <script language="javascript" type="text/javascript" src="/static/new/javascript/ctl_graph.js"></script>
 {% endblock %}
+
diff --git a/wqflask/wqflask/templates/ctl_setup.html b/wqflask/wqflask/templates/ctl_setup.html
index a05379a8..a7ad5759 100644
--- a/wqflask/wqflask/templates/ctl_setup.html
+++ b/wqflask/wqflask/templates/ctl_setup.html
@@ -11,7 +11,13 @@
     Please make sure you select enough traits to perform CTL. Your collection needs to contain at least 2 different traits. You provided {{request.form['trait_list'].split(',')|length}} traits as input.
   </div>
   {% else %}
-  <h1>CTL analysis parameters</h1>
+  <h1>CTL analysis</h1>
+  CTL analysis is published as open source software, if you are using this method in your publications, please cite:<br><br>
+  Arends D, Li Y, Brockmann GA, Jansen RC, Williams RW, Prins P<br>
+  Correlation trait locus (CTL) mapping: Phenotype network inference subject to genotype.<br>
+  The Journal of Open Source Software (2016)<br>
+  Published in <a href="http://joss.theoj.org/papers/10.21105/joss.00087"><img src="http://joss.theoj.org/papers/10.21105/joss.00087/status.svg"></a>
+  <br><br>
   {{(request.form['trait_list'].split(',')|length)}} traits as input
 
   <form action="/ctl_results" method="post" class="form-horizontal">