diff options
| -rwxr-xr-x | wqflask/utility/webqtlUtil.py | 2 | ||||
| -rw-r--r--[-rwxr-xr-x] | wqflask/wqflask/correlation/show_corr_results.py | 546 | ||||
| -rw-r--r-- | wqflask/wqflask/static/new/javascript/show_trait.js | 6 | ||||
| -rwxr-xr-x | wqflask/wqflask/templates/show_trait.html | 2 | ||||
| -rwxr-xr-x | wqflask/wqflask/templates/show_trait_details.html | 23 | ||||
| -rwxr-xr-x | wqflask/wqflask/templates/show_trait_mapping_tools.html | 172 |
6 files changed, 467 insertions, 284 deletions
diff --git a/wqflask/utility/webqtlUtil.py b/wqflask/utility/webqtlUtil.py index f842dde0..1108614b 100755 --- a/wqflask/utility/webqtlUtil.py +++ b/wqflask/utility/webqtlUtil.py @@ -509,7 +509,7 @@ def calCorrelationRank(xVals,yVals,N): j = 0 for i in range(len(xVals)): - if xVals[i]!= None and yVals[i]!= None: + if (xVals[i]!= None and yVals[i]!= None) and (xVals[i] != "None" and yVals[i] != "None"): XX.append((j,xVals[i])) YY.append((j,yVals[i])) j = j+1 diff --git a/wqflask/wqflask/correlation/show_corr_results.py b/wqflask/wqflask/correlation/show_corr_results.py index 98596ca4..0795f113 100755..100644 --- a/wqflask/wqflask/correlation/show_corr_results.py +++ b/wqflask/wqflask/correlation/show_corr_results.py @@ -50,6 +50,7 @@ from dbFunction import webqtlDatabaseFunction import utility.webqtlUtil #this is for parallel computing only. from wqflask.correlation import correlation_functions from utility.benchmark import Bench +import utility.webqtlUtil from MySQLdb import escape_string as escape @@ -159,6 +160,9 @@ class CorrelationResults(object): self.correlation_data = {} + db_filename = self.getFileName(target_db_name = self.target_dataset.name) + cache_available = db_filename in os.listdir(webqtlConfig.TEXTDIR) + if self.corr_type == "tissue": self.trait_symbol_dict = self.dataset.retrieve_genes("Symbol") @@ -174,9 +178,25 @@ class CorrelationResults(object): self.get_sample_r_and_p_values(trait, self.target_dataset.trait_data[trait]) elif self.corr_type == "sample": - # print("self.target_dataset.trait_data: %d" % len(self.target_dataset.trait_data)) - for trait, values in self.target_dataset.trait_data.iteritems(): - self.get_sample_r_and_p_values(trait, values) + if self.dataset.type == "ProbeSet" and cache_available: + dataset_file = open(webqtlConfig.TEXTDIR+db_filename,'r') + + #XZ, 01/08/2009: read the first line + line = dataset_file.readline() + dataset_strains = webqtlUtil.readLineCSV(line)[1:] + + self.this_trait_vals = [] + for item in dataset_strains: + if item in self.sample_data: + self.this_trait_vals.append(self.sample_data[item]) + else: + self.this_trait_vals.append("None") + num_overlap = len(self.this_trait_vals) + + self.do_parallel_correlation(db_filename, num_overlap) + else: + for trait, values in self.target_dataset.trait_data.iteritems(): + self.get_sample_r_and_p_values(trait, values) self.correlation_data = collections.OrderedDict(sorted(self.correlation_data.items(), key=lambda t: -abs(t[1][0]))) @@ -308,7 +328,7 @@ class CorrelationResults(object): #traitList = self.correlate() - #_log.info("Done doing correlation calculation") + #print("Done doing correlation calculation") ############################################################################################################################################ @@ -521,27 +541,125 @@ class CorrelationResults(object): """ - # print("len(self.sample_data):", len(self.sample_data)) - - this_trait_vals = [] + self.this_trait_vals = [] target_vals = [] for index, sample in enumerate(self.target_dataset.samplelist): if sample in self.sample_data: sample_value = self.sample_data[sample] target_sample_value = target_samples[index] - this_trait_vals.append(sample_value) + self.this_trait_vals.append(sample_value) target_vals.append(target_sample_value) - this_trait_vals, target_vals, num_overlap = corr_result_helpers.normalize_values( - this_trait_vals, target_vals) + self.this_trait_vals, target_vals, num_overlap = corr_result_helpers.normalize_values(self.this_trait_vals, target_vals) #ZS: 2015 could add biweight correlation, see http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3465711/ if self.corr_method == 'pearson': - sample_r, sample_p = scipy.stats.pearsonr(this_trait_vals, target_vals) + sample_r, sample_p = scipy.stats.pearsonr(self.this_trait_vals, target_vals) else: - sample_r, sample_p = scipy.stats.spearmanr(this_trait_vals, target_vals) + sample_r, sample_p = scipy.stats.spearmanr(self.this_trait_vals, target_vals) self.correlation_data[trait] = [sample_r, sample_p, num_overlap] + + + """ + correlations = [] + + #XZ: Use the fast method only for probeset dataset, and this dataset must have been created. + #XZ: Otherwise, use original method + #print("Entering correlation") + + #db_filename = self.getFileName(target_db_name=self.target_db_name) + # + #cache_available = db_filename in os.listdir(webqtlConfig.TEXTDIR) + + # If the cache file exists, do a cached correlation for probeset data + if self.dataset.type == "ProbeSet": +# if self.method in [METHOD_SAMPLE_PEARSON, METHOD_SAMPLE_RANK] and cache_available: +# traits = do_parallel_correlation() +# +# else: + + traits = self.get_traits(self.vals) + + for trait in traits: + trait.calculate_correlation(vals, self.method) + + self.record_count = len(traits) #ZS: This isn't a good way to get this value, so I need to change it later + + #XZ, 3/31/2010: Theoretically, we should create one function 'comTissueCorr' + #to compare each trait by their tissue corr p values. + #But because the tissue corr p values are generated by permutation test, + #the top ones always have p value 0. So comparing p values actually does nothing. + #In addition, for the tissue data in our database, the N is always the same. + #So it's safe to compare with tissue corr statistic value. + #That's the same as literature corr. + #if self.method in [METHOD_LIT, METHOD_TISSUE_PEARSON, METHOD_TISSUE_RANK] and self.gene_id: + # traits.sort(webqtlUtil.cmpLitCorr) + #else: + #if self.method in TISSUE_METHODS: + # sort(traits, key=lambda A: math.fabs(A.tissue_corr)) + #elif self.method == METHOD_LIT: + # traits.sort(traits, key=lambda A: math.fabs(A.lit_corr)) + #else: + traits = sortTraitCorrelations(traits, self.method) + + # Strip to the top N correlations + traits = traits[:min(self.returnNumber, len(traits))] + + addLiteratureCorr = False + addTissueCorr = False + + trait_list = [] + for trait in traits: + db_trait = webqtlTrait(db=self.db, name=trait.name, cursor=self.cursor) + db_trait.retrieveInfo( QTL='Yes' ) + + db_trait.Name = trait.name + db_trait.corr = trait.correlation + db_trait.nOverlap = trait.overlap + db_trait.corrPValue = trait.p_value + + # NL, 07/19/2010 + # js function changed, add a new parameter rankOrder for js function 'showTissueCorrPlot' + db_trait.RANK_ORDER = self.RANK_ORDERS[self.method] + + #XZ, 26/09/2008: Method is 4 or 5. Have fetched tissue corr, but no literature correlation yet. + if self.method in TISSUE_METHODS: + db_trait.tissueCorr = trait.tissue_corr + db_trait.tissuePValue = trait.p_tissue + addTissueCorr = True + + + #XZ, 26/09/2008: Method is 3, Have fetched literature corr, but no tissue corr yet. + elif self.method == METHOD_LIT: + db_trait.LCorr = trait.lit_corr + db_trait.mouse_geneid = self.translateToMouseGeneID(self.species, db_trait.geneid) + addLiteratureCorr = True + + #XZ, 26/09/2008: Method is 1 or 2. Have NOT fetched literature corr and tissue corr yet. + # Phenotype data will not have geneid, and neither will some probes + # we need to handle this because we will get an attribute error + else: + if self.input_trait_mouse_gene_id and self.db.type=="ProbeSet": + addLiteratureCorr = True + if self.trait_symbol and self.db.type=="ProbeSet": + addTissueCorr = True + + trait_list.append(db_trait) + + if addLiteratureCorr: + trait_list = self.getLiteratureCorrelationByList(self.input_trait_mouse_gene_id, + self.species, trait_list) + if addTissueCorr: + trait_list = self.getTissueCorrelationByList( + primaryTraitSymbol = self.trait_symbol, + traitList = trait_list, + TissueProbeSetFreezeId = TISSUE_MOUSE_DB, + method=self.method) + + return trait_list + """ + def do_tissue_corr_for_all_traits_2(self): """Comments Possibly Out of Date!!!!! @@ -670,38 +788,6 @@ class CorrelationResults(object): # except: return False - def get_all_dataset_data(self): - - """ - SELECT ProbeSet.Name, T128.value, T129.value, T130.value, T131.value, T132.value, T134.value, T135.value, T138.value, T139.value, T140.value, T141.value, T142.value, T144 - .value, T145.value, T147.value, T148.value, T149.value, T487.value, T919.value, T920.value, T922.value - FROM (ProbeSet, ProbeSetXRef, ProbeSetFreeze) - left join ProbeSetData as T128 on T128.Id = ProbeSetXRef.DataId and T128.StrainId=128 - left join ProbeSetData as T129 on T129.Id = ProbeSetXRef.DataId and T129.StrainId=129 - left join ProbeSetData as T130 on T130.Id = ProbeSetXRef.DataId and T130.StrainId=130 - left join ProbeSetData as T131 on T131.Id = ProbeSetXRef.DataId and T131.StrainId=131 - left join ProbeSetData as T132 on T132.Id = ProbeSetXRef.DataId and T132.StrainId=132 - left join ProbeSetData as T134 on T134.Id = ProbeSetXRef.DataId and T134.StrainId=134 - left join ProbeSetData as T135 on T135.Id = ProbeSetXRef.DataId and T135.StrainId=135 - left join ProbeSetData as T138 on T138.Id = ProbeSetXRef.DataId and T138.StrainId=138 - left join ProbeSetData as T139 on T139.Id = ProbeSetXRef.DataId and T139.StrainId=139 - left join ProbeSetData as T140 on T140.Id = ProbeSetXRef.DataId and T140.StrainId=140 - left join ProbeSetData as T141 on T141.Id = ProbeSetXRef.DataId and T141.StrainId=141 - left join ProbeSetData as T142 on T142.Id = ProbeSetXRef.DataId and T142.StrainId=142 - left join ProbeSetData as T144 on T144.Id = ProbeSetXRef.DataId and T144.StrainId=144 - left join ProbeSetData as T145 on T145.Id = ProbeSetXRef.DataId and T145.StrainId=145 - left join ProbeSetData as T147 on T147.Id = ProbeSetXRef.DataId and T147.StrainId=147 - left join ProbeSetData as T148 on T148.Id = ProbeSetXRef.DataId and T148.StrainId=148 - left join ProbeSetData as T149 on T149.Id = ProbeSetXRef.DataId and T149.StrainId=149 - left join ProbeSetData as T487 on T487.Id = ProbeSetXRef.DataId and T487.StrainId=487 - left join ProbeSetData as T919 on T919.Id = ProbeSetXRef.DataId and T919.StrainId=919 - left join ProbeSetData as T920 on T920.Id = ProbeSetXRef.DataId and T920.StrainId=920 - left join ProbeSetData as T922 on T922.Id = ProbeSetXRef.DataId and T922.StrainId=922 - WHERE ProbeSetXRef.ProbeSetFreezeId = ProbeSetFreeze.Id and - ProbeSetFreeze.Name = 'HC_M2_0606_P' and - ProbeSet.Id = ProbeSetXRef.ProbeSetId order by ProbeSet.Id - """ - def process_samples(self, start_vars, sample_names, excluded_samples=None): if not excluded_samples: excluded_samples = () @@ -990,59 +1076,7 @@ class CorrelationResults(object): totalTraits = len(traits) #XZ, 09/18/2008: total trait number return traits - - - def do_parallel_correlation(self): - _log.info("Invoking parallel computing") - input_line_list = datasetFile.readlines() - _log.info("Read lines from the file") - all_line_number = len(input_line_list) - - step = 1000 - job_number = math.ceil( float(all_line_number)/step ) - - job_input_lists = [] - - _log.info("Configuring jobs") - - for job_index in range( int(job_number) ): - starti = job_index*step - endi = min((job_index+1)*step, all_line_number) - - one_job_input_list = [] - - for i in range( starti, endi ): - one_job_input_list.append( input_line_list[i] ) - - job_input_lists.append( one_job_input_list ) - - _log.info("Creating pp servers") - - ppservers = () - # Creates jobserver with automatically detected number of workers - job_server = pp.Server(ppservers=ppservers) - - _log.info("Done creating servers") - - jobs = [] - results = [] - - _log.info("Starting parallel computation, submitting jobs") - for one_job_input_list in job_input_lists: #pay attention to modules from outside - jobs.append( job_server.submit(func=compute_corr, args=(nnCorr, _newvals, one_job_input_list, self.method), depfuncs=(), modules=("utility.webqtlUtil",)) ) - _log.info("Done submitting jobs") - - for one_job in jobs: - one_result = one_job() - results.append( one_result ) - - _log.info("Acquiring results") - - for one_result in results: - for one_traitinfo in one_result: - allcorrelations.append( one_traitinfo ) - - _log.info("Appending the results") + def calculate_corr_for_all_tissues(self, tissue_dataset_id=None): symbol_corr_dict = {} @@ -1067,10 +1101,7 @@ class CorrelationResults(object): # SymbolValueDict) return (symbolCorrDict, symbolPvalueDict) - datasetFile.close() - totalTraits = len(allcorrelations) - _log.info("Done correlating using the fast method") - + def correlate(self): self.correlation_data = collections.defaultdict(list) @@ -1085,107 +1116,254 @@ class CorrelationResults(object): values_2.append(target_value) correlation = calCorrelation(values_1, values_2) self.correlation_data[trait] = correlation + + def getFileName(self, target_db_name): ### dcrowell August 2008 + """Returns the name of the reference database file with which correlations are calculated. + Takes argument cursor which is a cursor object of any instance of a subclass of templatePage + Used by correlationPage""" + + dataset_id = str(self.target_dataset.id) + dataset_fullname = self.target_dataset.fullname.replace(' ','_') + dataset_fullname = dataset_fullname.replace('/','_') + FileName = 'ProbeSetFreezeId_' + dataset_id + '_FullName_' + dataset_fullname + '.txt' - """ - correlations = [] - - #XZ: Use the fast method only for probeset dataset, and this dataset must have been created. - #XZ: Otherwise, use original method - #_log.info("Entering correlation") - - #db_filename = self.getFileName(target_db_name=self.target_db_name) - # - #cache_available = db_filename in os.listdir(webqtlConfig.TEXTDIR) - - # If the cache file exists, do a cached correlation for probeset data - if self.dataset.type == "ProbeSet": -# if self.method in [METHOD_SAMPLE_PEARSON, METHOD_SAMPLE_RANK] and cache_available: -# traits = do_parallel_correlation() -# -# else: - - traits = self.get_traits(self.vals) + return FileName + + def do_parallel_correlation(self, db_filename, num_overlap): + + #XZ, 01/14/2009: This method is for parallel computing only. + #XZ: It is supposed to be called when "Genetic Correlation, Pearson's r" (method 1) + #XZ: or "Genetic Correlation, Spearman's rho" (method 2) is selected + def compute_corr(input_nnCorr, input_trait, input_list, corr_method): + + import math + import reaper + + def calCorrelation(dbdata,userdata,N): + X = [] + Y = [] + for i in range(N): + if (dbdata[i] != None and userdata[i] != None) and (dbdata[i] != "None" and userdata[i] != "None"): + X.append(float(dbdata[i])) + Y.append(float(userdata[i])) + NN = len(X) + if NN <6: + return (0.0,NN) + sx = reduce(lambda x,y:x+y,X,0.0) + sy = reduce(lambda x,y:x+y,Y,0.0) + meanx = sx/NN + meany = sy/NN + xyd = 0.0 + sxd = 0.0 + syd = 0.0 + for i in range(NN): + xyd += (X[i] - meanx)*(Y[i]-meany) + sxd += (X[i] - meanx)*(X[i] - meanx) + syd += (Y[i] - meany)*(Y[i] - meany) + try: + corr = xyd/(math.sqrt(sxd)*math.sqrt(syd)) + except: + corr = 0 + return (corr,NN) + + def calCorrelationRank(xVals,yVals,N): + """ + Calculated Spearman Ranked Correlation. The algorithm works + by setting all tied ranks to the average of those ranks (for + example, if ranks 5-10 all have the same value, each will be set + to rank 7.5). + """ + + XX = [] + YY = [] + j = 0 + + for i in range(len(xVals)): + if (xVals[i]!= None and yVals[i]!= None) and (xVals[i] != "None" and yVals[i] != "None"): + XX.append((j,float(xVals[i]))) + YY.append((j,float(yVals[i]))) + j = j+1 + + NN = len(XX) + if NN <6: + return (0.0,NN) + XX.sort(cmpOrder2) + YY.sort(cmpOrder2) + X = [0]*NN + Y = [0]*NN + + j = 1 + rank = 0.0 + t = 0.0 + sx = 0.0 + + while j < NN: + + if XX[j][1] != XX[j-1][1]: + X[XX[j-1][0]] = j + j = j+1 - for trait in traits: - trait.calculate_correlation(vals, self.method) + else: + jt = j+1 + ji = j + for jt in range(j+1, NN): + if (XX[jt][1] != XX[j-1][1]): + break + rank = 0.5*(j+jt) + for ji in range(j-1, jt): + X[XX[ji][0]] = rank + t = jt-j + sx = sx + (t*t*t-t) + if (jt == NN-1): + if (XX[jt][1] == XX[j-1][1]): + X[XX[NN-1][0]] = rank + j = jt+1 + + if j == NN: + if X[XX[NN-1][0]] == 0: + X[XX[NN-1][0]] = NN + + j = 1 + rank = 0.0 + t = 0.0 + sy = 0.0 + + while j < NN: + + if YY[j][1] != YY[j-1][1]: + Y[YY[j-1][0]] = j + j = j+1 + else: + jt = j+1 + ji = j + for jt in range(j+1, NN): + if (YY[jt][1] != YY[j-1][1]): + break + rank = 0.5*(j+jt) + for ji in range(j-1, jt): + Y[YY[ji][0]] = rank + t = jt - j + sy = sy + (t*t*t-t) + if (jt == NN-1): + if (YY[jt][1] == YY[j-1][1]): + Y[YY[NN-1][0]] = rank + j = jt+1 + + if j == NN: + if Y[YY[NN-1][0]] == 0: + Y[YY[NN-1][0]] = NN + + D = 0.0 + + for i in range(NN): + D += (X[i]-Y[i])*(X[i]-Y[i]) + + fac = (1.0 -sx/(NN*NN*NN-NN))*(1.0-sy/(NN*NN*NN-NN)) + + return ((1-(6.0/(NN*NN*NN-NN))*(D+(sx+sy)/12.0))/math.sqrt(fac),NN) + + # allcorrelations = [] + + correlation_data = {} + for i, line in enumerate(input_list): + if i == 0: + continue + tokens = line.split('","') + tokens[-1] = tokens[-1][:-2] #remove the last " + tokens[0] = tokens[0][1:] #remove the first " + + traitdataName = tokens[0] + database_trait = tokens[1:] + + #print("database_trait:", database_trait) + + #ZS: 2015 could add biweight correlation, see http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3465711/ + # if corr_method == 'pearson': + # sample_r, sample_p = scipy.stats.pearsonr(input_trait, database_trait) + # else: + # sample_r, sample_p = scipy.stats.spearmanr(input_trait, database_trait) + + if corr_method == "pearson": #XZ: Pearson's r + sample_r, nOverlap = calCorrelation(input_trait, database_trait, input_nnCorr) + else: #XZ: Spearman's rho + sample_r, nOverlap = calCorrelationRank(input_trait, database_trait, input_nnCorr) + + #XZ: calculate corrPValue + if nOverlap < 3: + sample_p = 1.0 + else: + if abs(sample_r) >= 1.0: + sample_p = 0.0 + else: + z_value = 0.5*math.log((1.0+sample_r)/(1.0-sample_r)) + z_value = z_value*math.sqrt(nOverlap-3) + sample_p = 2.0*(1.0 - reaper.normp(abs(z_value))) + + correlation_data[traitdataName] = [sample_r, sample_p, nOverlap] + + # traitinfo = [traitdataName, sample_r, nOverlap] + # allcorrelations.append(traitinfo) - self.record_count = len(traits) #ZS: This isn't a good way to get this value, so I need to change it later + return correlation_data + # return allcorrelations + + + datasetFile = open(webqtlConfig.TEXTDIR+db_filename,'r') + + print("Invoking parallel computing") + input_line_list = datasetFile.readlines() + print("Read lines from the file") + all_line_number = len(input_line_list) - #XZ, 3/31/2010: Theoretically, we should create one function 'comTissueCorr' - #to compare each trait by their tissue corr p values. - #But because the tissue corr p values are generated by permutation test, - #the top ones always have p value 0. So comparing p values actually does nothing. - #In addition, for the tissue data in our database, the N is always the same. - #So it's safe to compare with tissue corr statistic value. - #That's the same as literature corr. - #if self.method in [METHOD_LIT, METHOD_TISSUE_PEARSON, METHOD_TISSUE_RANK] and self.gene_id: - # traits.sort(webqtlUtil.cmpLitCorr) - #else: - #if self.method in TISSUE_METHODS: - # sort(traits, key=lambda A: math.fabs(A.tissue_corr)) - #elif self.method == METHOD_LIT: - # traits.sort(traits, key=lambda A: math.fabs(A.lit_corr)) - #else: - traits = sortTraitCorrelations(traits, self.method) + step = 1000 + job_number = math.ceil( float(all_line_number)/step ) - # Strip to the top N correlations - traits = traits[:min(self.returnNumber, len(traits))] + print("JOB NUMBER", job_number) + + job_input_lists = [] - addLiteratureCorr = False - addTissueCorr = False + print("Configuring jobs") - trait_list = [] - for trait in traits: - db_trait = webqtlTrait(db=self.db, name=trait.name, cursor=self.cursor) - db_trait.retrieveInfo( QTL='Yes' ) + for job_index in range( int(job_number) ): + starti = job_index*step + endi = min((job_index+1)*step, all_line_number) - db_trait.Name = trait.name - db_trait.corr = trait.correlation - db_trait.nOverlap = trait.overlap - db_trait.corrPValue = trait.p_value + one_job_input_list = [] - # NL, 07/19/2010 - # js function changed, add a new parameter rankOrder for js function 'showTissueCorrPlot' - db_trait.RANK_ORDER = self.RANK_ORDERS[self.method] + for i in range( starti, endi ): + one_job_input_list.append( input_line_list[i] ) - #XZ, 26/09/2008: Method is 4 or 5. Have fetched tissue corr, but no literature correlation yet. - if self.method in TISSUE_METHODS: - db_trait.tissueCorr = trait.tissue_corr - db_trait.tissuePValue = trait.p_tissue - addTissueCorr = True + job_input_lists.append( one_job_input_list ) + print("Creating pp servers") - #XZ, 26/09/2008: Method is 3, Have fetched literature corr, but no tissue corr yet. - elif self.method == METHOD_LIT: - db_trait.LCorr = trait.lit_corr - db_trait.mouse_geneid = self.translateToMouseGeneID(self.species, db_trait.geneid) - addLiteratureCorr = True + ppservers = () + # Creates jobserver with automatically detected number of workers + job_server = pp.Server(ppservers=ppservers) - #XZ, 26/09/2008: Method is 1 or 2. Have NOT fetched literature corr and tissue corr yet. - # Phenotype data will not have geneid, and neither will some probes - # we need to handle this because we will get an attribute error - else: - if self.input_trait_mouse_gene_id and self.db.type=="ProbeSet": - addLiteratureCorr = True - if self.trait_symbol and self.db.type=="ProbeSet": - addTissueCorr = True + print("Done creating servers") - trait_list.append(db_trait) + jobs = [] + results = [] - if addLiteratureCorr: - trait_list = self.getLiteratureCorrelationByList(self.input_trait_mouse_gene_id, - self.species, trait_list) - if addTissueCorr: - trait_list = self.getTissueCorrelationByList( - primaryTraitSymbol = self.trait_symbol, - traitList = trait_list, - TissueProbeSetFreezeId = TISSUE_MOUSE_DB, - method=self.method) + print("Starting parallel computation, submitting jobs") + for one_job_input_list in job_input_lists: #pay attention to modules from outside + jobs.append( job_server.submit(func=compute_corr, args=(num_overlap, self.this_trait_vals, one_job_input_list, self.corr_method), depfuncs=(), modules=("webqtlUtil",)) ) + print("Done submitting jobs") - return trait_list - """ + for one_job in jobs: + one_result = one_job() + self.correlation_data.update(one_result) + # one_result = one_job() + # results.append( one_result ) + #print("CORRELATION DATA:", self.correlation_data) + + # print("Acquiring results") + # for one_result in results: + # for one_traitinfo in one_result: + # allcorrelations.append( one_traitinfo ) diff --git a/wqflask/wqflask/static/new/javascript/show_trait.js b/wqflask/wqflask/static/new/javascript/show_trait.js index 2fa77ae0..5d0fa589 100644 --- a/wqflask/wqflask/static/new/javascript/show_trait.js +++ b/wqflask/wqflask/static/new/javascript/show_trait.js @@ -313,6 +313,12 @@ return $("#trait_data_form").submit(); }; + submit_corr = function(){ + var url; + url = "/corr_compute"; + return submit_special(url); + }; + $(".corr_compute").on("click", (function(_this) { return function() { var url; diff --git a/wqflask/wqflask/templates/show_trait.html b/wqflask/wqflask/templates/show_trait.html index 64638fc7..5e2dc6fa 100755 --- a/wqflask/wqflask/templates/show_trait.html +++ b/wqflask/wqflask/templates/show_trait.html @@ -29,7 +29,7 @@ <h3>{{ this_trait.description_fmt }}</h3> </div> - <form method="post" target="_blank" action="/corr_compute" name="trait_page" id="trait_data_form" + <form method="post" action="/corr_compute" target="_blank" name="trait_page" id="trait_data_form" class="form-horizontal"> <div id="hidden_inputs"> <input type="hidden" name="trait_hmac" value="{{ data_hmac('{}:{}'.format(this_trait.name, dataset.name)) }}"> diff --git a/wqflask/wqflask/templates/show_trait_details.html b/wqflask/wqflask/templates/show_trait_details.html index 95a3b967..d5fb0cf2 100755 --- a/wqflask/wqflask/templates/show_trait_details.html +++ b/wqflask/wqflask/templates/show_trait_details.html @@ -35,8 +35,7 @@ <tr> <td>Target Score</td> <td> - <a href="/blatInfo.html" target="_blank" - title="Values higher than 2 for the specificity are good"> + <a href="http://genenetwork.org/blatInfo.html" title="Values higher than 2 for the specificity are good"> BLAT Specificity </a>: {{ "%0.3f" | format(this_trait.probe_set_specificity|float) }} @@ -51,25 +50,25 @@ <td>Resource Links</td> <td> {% if this_trait.geneid != None %} - <a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=gene&cmd=Retrieve&dopt=Graphics&list_uids={{ this_trait.geneid }}" target="_blank" title="Info from NCBI Entrez Gene"> + <a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=gene&cmd=Retrieve&dopt=Graphics&list_uids={{ this_trait.geneid }}" title="Info from NCBI Entrez Gene"> Gene </a> {% endif %} {% if this_trait.omim != None %} - <a href="http://www.ncbi.nlm.nih.gov/omim/{{ this_trait.omim }}" target="_blank" title="Summary from On Mendelion Inheritance in Man"> + <a href="http://www.ncbi.nlm.nih.gov/omim/{{ this_trait.omim }}" title="Summary from On Mendelion Inheritance in Man"> OMIM </a> {% endif %} {% if this_trait.genbankid != None %} - <a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=Nucleotide&cmd=search&doptcmdl=DocSum&term={{ this_trait.genbankid }}" target="_blank" title="Find the original GenBank sequence used to design the probes"> + <a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=Nucleotide&cmd=search&doptcmdl=DocSum&term={{ this_trait.genbankid }}" title="Find the original GenBank sequence used to design the probes"> GenBank </a> {% endif %} {% if this_trait.symbol != None %} - <a href="http://www.genotation.org/Getd2g.pl?gene_list={{ this_trait.symbol }}" target="_blank" title="Related descriptive, genomic, clinical, functional and drug-therapy information"> + <a href="http://www.genotation.org/Getd2g.pl?gene_list={{ this_trait.symbol }}" title="Related descriptive, genomic, clinical, functional and drug-therapy information"> Genotation </a> @@ -87,40 +86,40 @@ </a> {% if this_trait.dataset.type == 'ProbeSet' %} {% if this_trait.symbol != None %} - <a href="#redirect" onclick="window.open('http://www.genenetwork.org/webqtl/main.py?cmd=sch&gene={{ this_trait.symbol }}&alias=1&species={{ species_name }}')"> + <a href="http://www.genenetwork.org/webqtl/main.py?cmd=sch&gene={{ this_trait.symbol }}&alias=1&species={{ species_name }}"> <button type="button" class="btn btn-default" title="Find similar expression data"> <i class="icon-search"></i> Find </button> </a> {% endif %} {% if UCSC_BLAT_URL != "" %} - <a href="#redirect" onclick="window.open('{{ UCSC_BLAT_URL }}')"> + <a href="{{ UCSC_BLAT_URL }}"> <button type="button" class="btn btn-default" title="Check probe locations at UCSC"> <i class="icon-ok"></i> Verify </button> </a> {% endif %} {% if this_trait.symbol != None %} - <a href="#redirect" onclick="window.open('http://genenetwork.org/webqtl/main.py?FormID=geneWiki&symbol={{ this_trait.symbol }}')"> + <a href="http://genenetwork.org/webqtl/main.py?FormID=geneWiki&symbol={{ this_trait.symbol }}"> <button type="button" class="btn btn-default" title="Write or review comments about this gene"> <i class="icon-edit"></i> GeneWiki </button> </a> - <a href="#redirect" onclick="window.open('http://genenetwork.org/webqtl/main.py?FormID=SnpBrowserResultPage&submitStatus=1&diffAlleles=True&customStrain=True&geneName={{ this_trait.symbol }}')"> + <a href="http://genenetwork.org/webqtl/main.py?FormID=SnpBrowserResultPage&submitStatus=1&diffAlleles=True&customStrain=True&geneName={{ this_trait.symbol }}"> <button type="button" class="btn btn-default" title="View SNPs and Indels"> <i class="icon-road"></i> SNPs </button> </a> {% endif %} {% if UTHSC_BLAT_URL != "" %} - <a href="#redirect" onclick="window.open('{{ UTHSC_BLAT_URL }}')"> + <a href="{{ UTHSC_BLAT_URL }}"> <button type="button" class="btn btn-default" title="View probes, SNPs, and RNA-seq at UTHSC"> <i class="icon-eye-close"></i> RNA-seq </button> </a> {% endif %} {% if show_probes == "True" %} - <a href="#redirect" onclick="window.open('http://genenetwork.org/webqtl/main.py?FormID=showProbeInfo&database={{ this_trait.dataset.name }}&ProbeSetID={{ this_trait.name }}&CellID={{ this_trait.cellid }}&RISet={{ dataset.group.name }}&incparentsf1=ON')"> + <a href="http://genenetwork.org/webqtl/main.py?FormID=showProbeInfo&database={{ this_trait.dataset.name }}&ProbeSetID={{ this_trait.name }}&CellID={{ this_trait.cellid }}&RISet={{ dataset.group.name }}&incparentsf1=ON"> <button type="button" class="btn btn-default" title="Check sequence of probes"> <i class="icon-list"></i> Probes </button> diff --git a/wqflask/wqflask/templates/show_trait_mapping_tools.html b/wqflask/wqflask/templates/show_trait_mapping_tools.html index 067dfc67..3d9c2521 100755 --- a/wqflask/wqflask/templates/show_trait_mapping_tools.html +++ b/wqflask/wqflask/templates/show_trait_mapping_tools.html @@ -6,13 +6,13 @@ <ul class="nav nav-pills"> {% if use_pylmm_rqtl and not use_plink_gemma and dataset.group.species != "human" %} <li class="active"> - <a href="#pylmm" data-toggle="tab">pyLMM</a> + <a href="#interval_mapping" data-toggle="tab">Interval Mapping</a> </li> <li> - <a href="#rqtl_geno" data-toggle="tab">R/qtl</a> + <a href="#pylmm" data-toggle="tab">pyLMM</a> </li> <li> - <a href="#interval_mapping" data-toggle="tab">Interval Mapping</a> + <a href="#rqtl_geno" data-toggle="tab">R/qtl</a> </li> {% endif %} {% if use_plink_gemma %} @@ -30,7 +30,89 @@ <div class="tab-content"> {% if use_pylmm_rqtl and not use_plink_gemma and dataset.group.species != "human" %} - <div class="tab-pane active" id="pylmm"> + <div class="tab-pane active" id="interval_mapping"> + <div style="margin-top: 20px" class="form-horizontal"> + <div class="mapping_method_fields form-group"> + <label for="mapping_permutations" class="col-xs-3 control-label">Permutations</label> + <div style="margin-left: 20px;" class="col-xs-4 controls"> + <input name="num_perm_reaper" value="2000" type="text" class="form-control"> + </div> + </div> + <div class="mapping_method_fields form-group"> + <label for="mapping_bootstraps" class="col-xs-3 control-label">Bootstraps</label> + <div style="margin-left: 20px;" class="col-xs-4 controls"> + <input name="num_bootstrap" value="2000" type="text" class="form-control"> + </div> + </div> + <div class="mapping_method_fields form-group"> + <label for="control_for" class="col-xs-3 control-label">Control for</label> + <div style="margin-left: 20px;" class="col-xs-4 controls"> + {% if dataset.type == 'ProbeSet' and this_trait.locus_chr != "" %} + <input name="control_reaper" value="{{ nearest_marker }}" type="text" style="width: 160px;" class="form-control" /> + {% else %} + <input name="control_reaper" value="" type="text" class="form-control" /> + {% endif %} + <label class="radio-inline"> + <input type="radio" name="do_control_reaper" value="true"> + Yes + </label> + <label class="radio-inline"> + <input type="radio" name="do_control_reaper" value="false" checked=""> + No + </label> + </div> + </div> + +<!-- + <div class="mapping_method_fields form-group"> + <label for="mapping_bootstraps" class="col-xs-3 control-label" title="Bootstrapping Resamples">Bootstrap Test (n=2000)</label> + <div class="col-xs-4 controls"> + <label> + <input type="checkbox" name="bootCheck" id="bootCheck"> Bootstrap Test (n=2000) + </label> + </div> + </div> + + <div class="mapping_method_fields form-group"> + <label style="text-align:left;" class="col-xs-12 control-label">Display Additive Effect</label> + <div class="col-xs-12 controls" id="display_additive_effect"> + <label class="radio-inline"> + <input type="radio" name="display_additive" id="display_additive" value="yes" checked=""> + Yes + </label> + <label class="radio-inline"> + <input type="radio" name="display_additive" id="display_additive" value="no"> + No + </label> + </div> + </div> +--> + + + <div class="mapping_method_fields form-group"> + <label style="text-align:left;" class="col-xs-12 control-label">Marker Regr.</label> + <div class="col-xs-12 controls"> + <label class="radio-inline"> + <input type="radio" name="manhattan_plot_reaper" value="True"> + Yes + </label> + <label class="radio-inline"> + <input type="radio" name="manhattan_plot_reaper" value="False" checked=""> + No + </label> + </div> + </div> + <div class="form-group"> + <div style="padding-left:15px;" class="controls"> + <button id="interval_mapping_compute" class="btn submit_special btn-primary" data-url="/marker_regression" title="Compute Interval Mapping"> + <i class="icon-ok-circle icon-white"></i> Compute + </button> + </div> + </div> + <!--<div id="alert_placeholder"></div>--> + </div> + </div> + <div class="tab-pane" id="pylmm"> <div style="margin-top: 20px" class="form-horizontal"> <div class="mapping_method_fields form-group"> <label for="mapping_permutations" class="col-xs-3 control-label">Permutations</label> @@ -179,88 +261,6 @@ </div> </div> </div> - <div class="tab-pane" id="interval_mapping"> - <div style="margin-top: 20px" class="form-horizontal"> - <div class="mapping_method_fields form-group"> - <label for="mapping_permutations" class="col-xs-3 control-label">Permutations</label> - <div style="margin-left: 20px;" class="col-xs-4 controls"> - <input name="num_perm_reaper" value="2000" type="text" class="form-control"> - </div> - </div> - <div class="mapping_method_fields form-group"> - <label for="mapping_bootstraps" class="col-xs-3 control-label">Bootstraps</label> - <div style="margin-left: 20px;" class="col-xs-4 controls"> - <input name="num_bootstrap" value="2000" type="text" class="form-control"> - </div> - </div> - <div class="mapping_method_fields form-group"> - <label for="control_for" class="col-xs-3 control-label">Control for</label> - <div style="margin-left: 20px;" class="col-xs-4 controls"> - {% if dataset.type == 'ProbeSet' and this_trait.locus_chr != "" %} - <input name="control_reaper" value="{{ nearest_marker }}" type="text" style="width: 160px;" class="form-control" /> - {% else %} - <input name="control_reaper" value="" type="text" class="form-control" /> - {% endif %} - <label class="radio-inline"> - <input type="radio" name="do_control_reaper" value="true"> - Yes - </label> - <label class="radio-inline"> - <input type="radio" name="do_control_reaper" value="false" checked=""> - No - </label> - </div> - </div> - -<!-- - <div class="mapping_method_fields form-group"> - <label for="mapping_bootstraps" class="col-xs-3 control-label" title="Bootstrapping Resamples">Bootstrap Test (n=2000)</label> - <div class="col-xs-4 controls"> - <label> - <input type="checkbox" name="bootCheck" id="bootCheck"> Bootstrap Test (n=2000) - </label> - </div> - </div> - - <div class="mapping_method_fields form-group"> - <label style="text-align:left;" class="col-xs-12 control-label">Display Additive Effect</label> - <div class="col-xs-12 controls" id="display_additive_effect"> - <label class="radio-inline"> - <input type="radio" name="display_additive" id="display_additive" value="yes" checked=""> - Yes - </label> - <label class="radio-inline"> - <input type="radio" name="display_additive" id="display_additive" value="no"> - No - </label> - </div> - </div> ---> - - - <div class="mapping_method_fields form-group"> - <label style="text-align:left;" class="col-xs-12 control-label">Marker Regr.</label> - <div class="col-xs-12 controls"> - <label class="radio-inline"> - <input type="radio" name="manhattan_plot_reaper" value="True"> - Yes - </label> - <label class="radio-inline"> - <input type="radio" name="manhattan_plot_reaper" value="False" checked=""> - No - </label> - </div> - </div> - <div class="form-group"> - <div style="padding-left:15px;" class="controls"> - <button id="interval_mapping_compute" class="btn submit_special btn-primary" data-url="/marker_regression" title="Compute Interval Mapping"> - <i class="icon-ok-circle icon-white"></i> Compute - </button> - </div> - </div> - <!--<div id="alert_placeholder"></div>--> - </div> - </div> {% endif %} {% if use_plink_gemma %} <div class="tab-pane" id="plink"> |