aboutsummaryrefslogtreecommitdiff
path: root/wqflask
diff options
context:
space:
mode:
Diffstat (limited to 'wqflask')
-rw-r--r--[-rwxr-xr-x]wqflask/wqflask/collect.py2
-rw-r--r--wqflask/wqflask/marker_regression/gemma_mapping.py2
-rw-r--r--[-rwxr-xr-x]wqflask/wqflask/marker_regression/marker_regression.py55
-rw-r--r--wqflask/wqflask/marker_regression/marker_regression_gn1.py20
-rw-r--r--wqflask/wqflask/templates/marker_regression_gn1.html8
-rw-r--r--[-rwxr-xr-x]wqflask/wqflask/views.py1
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',