diff options
Diffstat (limited to 'wqflask/base/data_set.py')
| -rwxr-xr-x | wqflask/base/data_set.py | 134 |
1 files changed, 101 insertions, 33 deletions
diff --git a/wqflask/base/data_set.py b/wqflask/base/data_set.py index fbe78d5d..2a79dc9c 100755 --- a/wqflask/base/data_set.py +++ b/wqflask/base/data_set.py @@ -23,6 +23,7 @@ import os import math import string import collections +import codecs import json import gzip @@ -156,38 +157,90 @@ class Markers(object): """Todo: Build in cacheing so it saves us reading the same file more than once""" def __init__(self, name): json_data_fh = open(os.path.join(webqtlConfig.NEWGENODIR + name + '.json')) - self.markers = json.load(json_data_fh) + markers = json.load(json_data_fh) + + for marker in markers: + if (marker['chr'] != "X") and (marker['chr'] != "Y"): + marker['chr'] = int(marker['chr']) + #else: + # marker['chr'] = 20 + print("Mb:", marker['Mb']) + marker['Mb'] = float(marker['Mb']) + + self.markers = markers + #print("self.markers:", self.markers) + def add_pvalues(self, p_values): - #print("length of self.markers:", len(self.markers)) - #print("length of p_values:", len(p_values)) - - # THIS IS only needed for the case when we are limiting the number of p-values calculated - if len(self.markers) < len(p_values): - self.markers = self.markers[:len(p_values)] - - for marker, p_value in itertools.izip(self.markers, p_values): - marker['p_value'] = p_value - if math.isnan(marker['p_value']): - print("p_value is:", marker['p_value']) - marker['lod_score'] = -math.log10(marker['p_value']) - #Using -log(p) for the LRS; need to ask Rob how he wants to get LRS from p-values - marker['lrs_value'] = -math.log10(marker['p_value']) * 4.61 - + print("length of self.markers:", len(self.markers)) + print("length of p_values:", len(p_values)) + if type(p_values) is list: + # THIS IS only needed for the case when we are limiting the number of p-values calculated + #if len(self.markers) > len(p_values): + # self.markers = self.markers[:len(p_values)] + + for marker, p_value in itertools.izip(self.markers, p_values): + if not p_value: + continue + marker['p_value'] = float(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']) + #Using -log(p) for the LRS; need to ask Rob how he wants to get LRS from p-values + marker['lrs_value'] = -math.log10(marker['p_value']) * 4.61 + elif type(p_values) is dict: + filtered_markers = [] + for marker in self.markers: + #print("marker[name]", marker['name']) + #print("p_values:", p_values) + if marker['name'] in p_values: + #print("marker {} IS in p_values".format(i)) + marker['p_value'] = p_values[marker['name']] + 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']) + #Using -log(p) for the LRS; need to ask Rob how he wants to get LRS from p-values + marker['lrs_value'] = -math.log10(marker['p_value']) * 4.61 + filtered_markers.append(marker) + #else: + #print("marker {} NOT in p_values".format(i)) + #self.markers.remove(marker) + #del self.markers[i] + self.markers = filtered_markers + + #for i, marker in enumerate(self.markers): + # if not 'p_value' in marker: + # #print("self.markers[i]", self.markers[i]) + # del self.markers[i] + # #self.markers.remove(self.markers[i]) class HumanMarkers(Markers): - def __init__(self, name): + def __init__(self, name, specified_markers = []): marker_data_fh = open(os.path.join(webqtlConfig.PYLMM_PATH + name + '.bim')) self.markers = [] for line in marker_data_fh: splat = line.strip().split() - marker = {} - marker['chr'] = int(splat[0]) - marker['name'] = splat[1] - marker['Mb'] = float(splat[3]) / 1000000 + #print("splat:", splat) + if len(specified_markers) > 0: + if splat[1] in specified_markers: + marker = {} + marker['chr'] = int(splat[0]) + marker['name'] = splat[1] + marker['Mb'] = float(splat[3]) / 1000000 + else: + continue + else: + marker = {} + marker['chr'] = int(splat[0]) + marker['name'] = splat[1] + marker['Mb'] = float(splat[3]) / 1000000 self.markers.append(marker) #print("markers is: ", pf(self.markers)) @@ -203,14 +256,15 @@ class HumanMarkers(Markers): # #Using -log(p) for the LRS; need to ask Rob how he wants to get LRS from p-values # marker['lrs_value'] = -math.log10(marker['p_value']) * 4.61 + #print("p_values2:", pf(p_values)) super(HumanMarkers, self).add_pvalues(p_values) - with Bench("deleting markers"): - markers = [] - for marker in self.markers: - if not marker['Mb'] <= 0 and not marker['chr'] == 0: - markers.append(marker) - self.markers = markers + #with Bench("deleting markers"): + # markers = [] + # for marker in self.markers: + # if not marker['Mb'] <= 0 and not marker['chr'] == 0: + # markers.append(marker) + # self.markers = markers @@ -230,7 +284,7 @@ class DatasetGroup(object): self.name = "BXD" self.f1list = None - self.parlist = None + self.parlist = None self.get_f1_parent_strains() #print("parents/f1s: {}:{}".format(self.parlist, self.f1list)) @@ -239,6 +293,8 @@ class DatasetGroup(object): self.incparentsf1 = False self.allsamples = None + def get_specified_markers(self, markers = []): + self.markers = HumanMarkers(self.name, markers) def get_markers(self): #print("self.species is:", self.species) @@ -450,8 +506,9 @@ class DataSet(object): else: self.samplelist = self.group.samplelist - if (self.group.parlist + self.group.f1list) in self.samplelist: - self.samplelist += self.group.parlist + self.group.f1list + if self.group.parlist != None and self.group.f1list != None: + if (self.group.parlist + self.group.f1list) in self.samplelist: + self.samplelist += self.group.parlist + self.group.f1list query = """ SELECT Strain.Name, Strain.Id FROM Strain, Species @@ -521,7 +578,11 @@ class DataSet(object): order by {}.Id """.format(*mescape(self.type, self.type, self.type, self.type, self.name, dataset_type, self.type, self.type, dataset_type)) + + #print("trait data query: ", query) + results = g.db.execute(query).fetchall() + #print("query results:", results) trait_sample_data.append(results) trait_count = len(trait_sample_data[0]) @@ -611,6 +672,7 @@ class PhenotypeDataSet(DataSet): def get_trait_info(self, trait_list, species = ''): for this_trait in trait_list: + if not this_trait.haveinfo: this_trait.retrieve_info(get_qtl_info=True) @@ -620,6 +682,7 @@ class PhenotypeDataSet(DataSet): #phenotype traits, then display the pre-publication description instead #of the post-publication description if this_trait.confidential: + this_trait.description_display = "" continue # for now if not webqtlUtil.hasAccessToConfidentialPhenotypeTrait( @@ -629,7 +692,12 @@ class PhenotypeDataSet(DataSet): description = this_trait.pre_publication_description - this_trait.description_display = description.strip() + if len(description) > 0: + this_trait.description_display = description.strip() + else: + this_trait.description_display = "" + + print("this_trait.description_display is:", this_trait.description_display) if not this_trait.year.isdigit(): this_trait.pubmed_text = "N/A" @@ -952,8 +1020,8 @@ class MrnaAssayDataSet(DataSet): #XZ, 12/08/2008: description #XZ, 06/05/2009: Rob asked to add probe target description - description_string = str(this_trait.description).strip() - target_string = str(this_trait.probe_target_description).strip() + description_string = unicode(str(this_trait.description).strip(codecs.BOM_UTF8), 'utf-8') + target_string = unicode(str(this_trait.probe_target_description).strip(codecs.BOM_UTF8), 'utf-8') if len(description_string) > 1 and description_string != 'None': description_display = description_string |