Fixed GN1 mapping plots so that Y axis and the Y coordinates of manhattan plot points are correct

Table filters markers so it can always be displayed now (previously was too large for GEMMA)

6 files changed, 38 insertions, 50 deletions

diff --git a/wqflask/wqflask/collect.py b/wqflask/wqflask/collect.py
index 750f4757..cd4c6fdc 100755..100644
--- a/wqflask/wqflask/collect.py
+++ b/wqflask/wqflask/collect.py
@@ -243,8 +243,6 @@ def list_collections():
                                )
     except:
         return redirect(url_for('view_collection'))
-        #return render_template("collections/view_anonymous.html",
-        #                        params = params)
 
 
 @app.route("/collections/remove", methods=('POST',))
diff --git a/wqflask/wqflask/marker_regression/gemma_mapping.py b/wqflask/wqflask/marker_regression/gemma_mapping.py
index 997b692d..cfcd4783 100644
--- a/wqflask/wqflask/marker_regression/gemma_mapping.py
+++ b/wqflask/wqflask/marker_regression/gemma_mapping.py
@@ -45,5 +45,5 @@ def parse_gemma_output(this_dataset):
                 included_markers.append(line.split("\t")[1])
                 p_values.append(float(line.split("\t")[10]))
 
-    print("p_values: ", p_values)
+    #print("p_values: ", p_values)
     return included_markers, p_values
\ No newline at end of file
diff --git a/wqflask/wqflask/marker_regression/marker_regression.py b/wqflask/wqflask/marker_regression/marker_regression.py
index c50b9d78..7adc0a2e 100755..100644
--- a/wqflask/wqflask/marker_regression/marker_regression.py
+++ b/wqflask/wqflask/marker_regression/marker_regression.py
@@ -176,6 +176,8 @@ class MarkerRegression(object):
                     if ('lod_score' in marker.keys()) or ('lrs_value' in marker.keys()):
                         self.qtl_results.append(marker)
 
+            self.trimmed_markers = trim_markers_for_table(results)
+			
             self.json_data['chr'] = []
             self.json_data['pos'] = []
             self.json_data['lod.hk'] = []
@@ -234,7 +236,7 @@ class MarkerRegression(object):
                                                                                                  self.dataset.group.name,
                                                                                                  self.dataset.group.name,
                                                                                                  self.dataset.group.name)
-        print("gemma_command:" + gemma_command)
+        #print("gemma_command:" + gemma_command)
         
         os.system(gemma_command)
         
@@ -628,10 +630,10 @@ class MarkerRegression(object):
         self.json_data['suggestive'] = self.suggestive
         self.json_data['significant'] = self.significant
 
-        print("samples:", trimmed_samples)
+        #print("samples:", trimmed_samples)
 
         if self.control != "" and self.do_control == "true":
-            print("CONTROL IS:", self.control)
+            #print("CONTROL IS:", self.control)
             reaper_results = genotype.regression(strains = trimmed_samples,
                                                           trait = trimmed_values,
                                                           control = str(self.control))
@@ -749,7 +751,7 @@ class MarkerRegression(object):
 
         top_lod_scores = []
 	
-        print("self.num_perm:", self.num_perm)
+        #print("self.num_perm:", self.num_perm)
 
         for permutation in range(int(self.num_perm)):
 
@@ -796,10 +798,10 @@ class MarkerRegression(object):
                     if p_value < lowest_p_value:
                         lowest_p_value = p_value
                 
-                print("lowest_p_value:", lowest_p_value)        
+                #print("lowest_p_value:", lowest_p_value)        
                 top_lod_scores.append(-math.log10(lowest_p_value))
 
-        print("top_lod_scores:", top_lod_scores)
+        #print("top_lod_scores:", top_lod_scores)
 
         self.suggestive = np.percentile(top_lod_scores, 67)
         self.significant = np.percentile(top_lod_scores, 95)
@@ -1012,6 +1014,21 @@ def create_snp_iterator_file(group):
     with gzip.open(snp_file_base, "wb") as fh:
         pickle.dump(data, fh, pickle.HIGHEST_PROTOCOL)
 
+def trim_markers_for_table(markers):
+    num_markers = len(markers)
+	
+    if 'lod_score' in markers[0].keys():
+        sorted_markers = sorted(markers, key=lambda k: k['lod_score'], reverse=True)
+    else:
+        sorted_markers = sorted(markers, key=lambda k: k['lrs_value'], reverse=True)
+    trimmed_sorted_markers = sorted_markers[:int(len(sorted_markers) * 0.001)]
+	
+    if len(trimmed_sorted_markers) < 50:
+        return sorted_markers
+    else:
+        return trimmed_sorted_markers
+
+
 def get_markers_from_csv(included_markers, p_values, group_name):
     marker_data_fh = open(os.path.join(webqtlConfig.PYLMM_PATH + group_name + '_markers.csv'))
     markers = []
@@ -1035,33 +1052,7 @@ def get_markers_from_csv(included_markers, p_values, group_name):
                 markers.append(marker)
                 break
 
-#    for line, p_value in itertools.izip(marker_data_fh, p_values):
-#        if not p_value or len(included_markers) < 1: 
-#            continue
-#        splat = line.strip().split()
-#        if splat[0] in included_markers:
-#            marker = {}
-#            marker['name'] = splat[0]
-#            marker['chr'] = int(splat[1])
-#            marker['Mb'] = float(splat[2])
-#            marker['p_value'] = p_value
-#            if math.isnan(marker['p_value']) or (marker['p_value'] <= 0):
-#                marker['lod_score'] = 0
-#                marker['lrs_value'] = 0
-#            else:
-#                marker['lod_score'] = -math.log10(marker['p_value'])
-#                marker['lrs_value'] = -math.log10(marker['p_value']) * 4.61
-#            markers.append(marker)
-#        else:
-#            continue
-
     return markers
-        
-
-#if __name__ == '__main__':
-#    import cPickle as pickle
-#    import gzip
-#    create_snp_iterator_file("HLC")
     
 if __name__ == '__main__':
     import cPickle as pickle
diff --git a/wqflask/wqflask/marker_regression/marker_regression_gn1.py b/wqflask/wqflask/marker_regression/marker_regression_gn1.py
index 01cee4f4..37e67d71 100644
--- a/wqflask/wqflask/marker_regression/marker_regression_gn1.py
+++ b/wqflask/wqflask/marker_regression/marker_regression_gn1.py
@@ -24,7 +24,6 @@
 #
 # Last updated by Zach 12/14/2010
 
-
 import time
 import string
 from math import *
@@ -187,6 +186,7 @@ class MarkerRegression(object):
             self.pair_scan = start_vars['pair_scan']
 
         self.js_data = start_vars['js_data']
+        self.trimmed_markers = start_vars['trimmed_markers'] #Top markers to display in table
 
         #ZS: Think I can just get all this from dataset object now
         #RISet and Species
@@ -210,6 +210,7 @@ class MarkerRegression(object):
         else:
             self._ucscDb = ""
 
+
         #####################################
         # Options
         #####################################
@@ -1838,17 +1839,17 @@ class MarkerRegression(object):
         #LRSTop is then defined to be above the LRSMax by enough to add one additional LRSScale increment.
         #if we are using a set-scale, then we set LRSTop to be the user's value, and LRSMax doesn't matter.
 
-        if self.LRS_LOD == 'LOD':
+        if self.LRS_LOD == 'LRS':
             lodm = self.LODFACTOR
         else:
             lodm = 1.0
  
         if self.lrsMax <= 0:  #sliding scale
-            if "lrs_value" in self.qtlresults[0]:
-                LRSMax = max([result['lrs_value'] for result in self.qtlresults])
+            if "lod_score" in self.qtlresults[0]:
+                LRSMax = max([result['lod_score'] for result in self.qtlresults])
                 #LRSMax = max(map(max, self.qtlresults)).lrs_value
             else: 
-                LRSMax = max([result['lod_score'] for result in self.qtlresults])
+                LRSMax = max([result['lrs_value'] for result in self.qtlresults])
                 #LRSMax = max(map(max, self.qtlresults)).lod_score
             #genotype trait will give infinite LRS
             LRSMax = min(LRSMax, webqtlConfig.MAXLRS)
@@ -1867,7 +1868,7 @@ class MarkerRegression(object):
             LRSScale = 2.5
         else:
             LRSScale = 1.0
-
+           
         LRSAxisList = Plot.frange(LRSScale, LRSMax/lodm, LRSScale)
         #make sure the user's value appears on the y-axis
         #update by NL 6-21-2011: round the LOD value to 100 when LRSMax is equal to 460
@@ -2004,8 +2005,8 @@ class MarkerRegression(object):
                     #    Yc = yZero - qtlresult[m].dominance*DominanceHeightThresh/dominanceMax
                     #    DominanceCoordXY.append((Xc, Yc))
                     m += 1
-                if self.manhattan_plot != True:
-                    canvas.drawPolygon(LRSCoordXY,edgeColor=thisLRSColor,closed=0, edgeWidth=lrsEdgeWidth, clipX=(xLeftOffset, xLeftOffset + plotWidth))
+        
+                    #canvas.drawPolygon(LRSCoordXY,edgeColor=thisLRSColor,closed=0, edgeWidth=lrsEdgeWidth, clipX=(xLeftOffset, xLeftOffset + plotWidth))
 
                 lineWidth = 1
                 if not self.multipleInterval and self.additiveChecked:
@@ -2068,7 +2069,8 @@ class MarkerRegression(object):
                                     canvas.drawLine(Xc0, yZero - (Yc0-yZero), Xc, yZero - (Yc-yZero), color=minusColor, width=lineWidth, clipX=(xLeftOffset, xLeftOffset + plotWidth))
                 
 
-        #canvas.drawPolygon(LRSCoordXY,edgeColor=thisLRSColor,closed=0, edgeWidth=lrsEdgeWidth, clipX=(xLeftOffset, xLeftOffset + plotWidth))
+        if self.manhattan_plot != True:
+		    canvas.drawPolygon(LRSCoordXY,edgeColor=thisLRSColor,closed=0, edgeWidth=lrsEdgeWidth, clipX=(xLeftOffset, xLeftOffset + plotWidth))
 
         ###draw additive scale
         if not self.multipleInterval and self.additiveChecked:
diff --git a/wqflask/wqflask/templates/marker_regression_gn1.html b/wqflask/wqflask/templates/marker_regression_gn1.html
index 58478758..11989ae7 100644
--- a/wqflask/wqflask/templates/marker_regression_gn1.html
+++ b/wqflask/wqflask/templates/marker_regression_gn1.html
@@ -96,7 +96,6 @@
         </div>
 
         </form>
-        {% if mapping_method != "gemma" %}
         <div style="width:48%;">
             <h2>
                 Results
@@ -117,9 +116,7 @@
                    </tr>
                 </thead>
                 <tbody>
-                    {% for marker in qtlresults %}
-                        {% if (LRS_LOD == "LOD" and marker.lod_score|float > cutoff|float) or
-                              (LRS_LOD == "LRS" and marker.lrs_value|float > cutoff|float) %}
+                    {% for marker in trimmed_markers %}
                         <tr>
                             <td>
                                 <input type="checkbox" name="selectCheck"
@@ -144,12 +141,10 @@
                                 </a>-->
                             </td>
                         </tr>
-                        {% endif %}
                     {% endfor %}
                 </tbody>
             </table>
         </div>
-        {% endif %}
     </div>
 
     <!-- End of body -->
@@ -195,6 +190,7 @@
                     { "type": "natural" },
                     { "type": "natural", "sWidth": "30%"}
                     ],
+                "order": [[1, "asc"]],
                 "buttons": [
                     'csv'
                 ],
diff --git a/wqflask/wqflask/views.py b/wqflask/wqflask/views.py
index 2af03f96..6f53a950 100755..100644
--- a/wqflask/wqflask/views.py
+++ b/wqflask/wqflask/views.py
@@ -341,6 +341,7 @@ def marker_regression_page():
         'trait_id',
         'dataset',
         'method',
+        'trimmed_markers',
         'selected_chr',
         'mapping_scale',
         'score_type',