diff options
| -rwxr-xr-x | wqflask/wqflask/show_trait/DataEditingPage.py | 389 |
1 files changed, 196 insertions, 193 deletions
diff --git a/wqflask/wqflask/show_trait/DataEditingPage.py b/wqflask/wqflask/show_trait/DataEditingPage.py index bb6156c3..affcd449 100755 --- a/wqflask/wqflask/show_trait/DataEditingPage.py +++ b/wqflask/wqflask/show_trait/DataEditingPage.py @@ -185,7 +185,10 @@ class DataEditingPage(templatePage): # # We'll get this part working later # print("Calling dispBasicStatistics") # self.dispBasicStatistics(fd, thisTrait) - # #self.dispMappingTools(fd, title4Body, thisTrait) + + self.build_correlation_tools(fd, thisTrait) + + # self.dispMappingTools(fd, title4Body, thisTrait) ############################# ## Trait Value Table @@ -1126,214 +1129,214 @@ class DataEditingPage(templatePage): #title2Body.append(submitTable) - def dispCorrelationTools(self, fd, title3Body, thisTrait): + def build_correlation_tools(self, fd, thisTrait): - _Species = webqtlDatabaseFunction.retrieveSpecies(cursor=self.cursor, RISet=fd.RISet) + #species = webqtlDatabaseFunction.retrieveSpecies(cursor=self.cursor, RISet=fd.RISet) RISetgp = fd.RISet + + # We're checking a string here! + assert isinstance(RISetgp, basestring), "We need a string type thing here" if RISetgp[:3] == 'BXD': RISetgp = 'BXD' if RISetgp: - sample_correlation = HT.Input(type='button',name='sample_corr', value=' Compute ', Class="button sample_corr") - lit_correlation = HT.Input(type='button',name='lit_corr', value=' Compute ', Class="button lit_corr") - tissue_correlation = HT.Input(type='button',name='tiss_corr', value=' Compute ', Class="button tiss_corr") - methodText = HT.Span("Calculate:", Class="ffl fwb fs12") - - databaseText = HT.Span("Database:", Class="ffl fwb fs12") - databaseMenu1 = HT.Select(name='database1') - databaseMenu2 = HT.Select(name='database2') - databaseMenu3 = HT.Select(name='database3') - - nmenu = 0 - self.cursor.execute('SELECT PublishFreeze.FullName,PublishFreeze.Name FROM \ - PublishFreeze,InbredSet WHERE PublishFreeze.InbredSetId = InbredSet.Id \ - and InbredSet.Name = "%s" and PublishFreeze.public > %d' % \ - (RISetgp,webqtlConfig.PUBLICTHRESH)) + #sample_correlation = HT.Input(type='button',name='sample_corr', value=' Compute ', Class="button sample_corr") + #lit_correlation = HT.Input(type='button',name='lit_corr', value=' Compute ', Class="button lit_corr") + #tissue_correlation = HT.Input(type='button',name='tiss_corr', value=' Compute ', Class="button tiss_corr") + #methodText = HT.Span("Calculate:", Class="ffl fwb fs12") + # + #databaseText = HT.Span("Database:", Class="ffl fwb fs12") + #databaseMenu1 = HT.Select(name='database1') + #databaseMenu2 = HT.Select(name='database2') + #databaseMenu3 = HT.Select(name='database3') + + dataset_menu = [] + print("[tape4] webqtlConfig.PUBLICTHRESH:", webqtlConfig.PUBLICTHRESH) + print("[tape4] type webqtlConfig.PUBLICTHRESH:", type(webqtlConfig.PUBLICTHRESH)) + self.cursor.execute('''SELECT PublishFreeze.FullName,PublishFreeze.Name FROM + PublishFreeze,InbredSet WHERE PublishFreeze.InbredSetId = InbredSet.Id + and InbredSet.Name = %s and PublishFreeze.public > %s''', + (RISetgp, webqtlConfig.PUBLICTHRESH)) for item in self.cursor.fetchall(): - databaseMenu1.append(item) - databaseMenu2.append(item) - databaseMenu3.append(item) - nmenu += 1 - self.cursor.execute('SELECT GenoFreeze.FullName,GenoFreeze.Name FROM GenoFreeze,\ - InbredSet WHERE GenoFreeze.InbredSetId = InbredSet.Id and InbredSet.Name = \ - "%s" and GenoFreeze.public > %d' % (RISetgp,webqtlConfig.PUBLICTHRESH)) + dataset_menu.append(dict(tissue=None, + datasets=item)) + + self.cursor.execute('''SELECT GenoFreeze.FullName,GenoFreeze.Name FROM GenoFreeze, + InbredSet WHERE GenoFreeze.InbredSetId = InbredSet.Id and InbredSet.Name = + %s and GenoFreeze.public > %s''', + (RISetgp, webqtlConfig.PUBLICTHRESH)) for item in self.cursor.fetchall(): - databaseMenu1.append(item) - databaseMenu2.append(item) - databaseMenu3.append(item) - nmenu += 1 + dataset_menu.append(dict(tissue=None, + datasets=item)) + #03/09/2009: Xiaodong changed the SQL query to order by Name as requested by Rob. self.cursor.execute('SELECT Id, Name FROM Tissue order by Name') for item in self.cursor.fetchall(): - TId, TName = item - databaseMenuSub = HT.Optgroup(label = '%s ------' % TName) - self.cursor.execute('SELECT ProbeSetFreeze.FullName,ProbeSetFreeze.Name FROM ProbeSetFreeze, ProbeFreeze, \ - InbredSet WHERE ProbeSetFreeze.ProbeFreezeId = ProbeFreeze.Id and ProbeFreeze.TissueId = %d and \ - ProbeSetFreeze.public > %d and ProbeFreeze.InbredSetId = InbredSet.Id and InbredSet.Name like "%s%%" \ - order by ProbeSetFreeze.CreateTime desc, ProbeSetFreeze.AvgId ' % (TId,webqtlConfig.PUBLICTHRESH, RISetgp)) - for item2 in self.cursor.fetchall(): - databaseMenuSub.append(item2) - nmenu += 1 - databaseMenu1.append(databaseMenuSub) - databaseMenu2.append(databaseMenuSub) - databaseMenu3.append(databaseMenuSub) - if nmenu: - if thisTrait and thisTrait.db != None: - databaseMenu1.selected.append(thisTrait.db.fullname) - databaseMenu2.selected.append(thisTrait.db.fullname) - databaseMenu3.selected.append(thisTrait.db.fullname) - - criteriaText = HT.Span("Return:", Class="ffl fwb fs12") - - criteriaMenu1 = HT.Select(name='criteria1', selected='500', onMouseOver="if (NS4 || IE4) activateEl('criterias', event);") - criteriaMenu1.append(('top 100','100')) - criteriaMenu1.append(('top 200','200')) - criteriaMenu1.append(('top 500','500')) - criteriaMenu1.append(('top 1000','1000')) - criteriaMenu1.append(('top 2000','2000')) - criteriaMenu1.append(('top 5000','5000')) - criteriaMenu1.append(('top 10000','10000')) - criteriaMenu1.append(('top 15000','15000')) - criteriaMenu1.append(('top 20000','20000')) - - criteriaMenu2 = HT.Select(name='criteria2', selected='500', onMouseOver="if (NS4 || IE4) activateEl('criterias', event);") - criteriaMenu2.append(('top 100','100')) - criteriaMenu2.append(('top 200','200')) - criteriaMenu2.append(('top 500','500')) - criteriaMenu2.append(('top 1000','1000')) - criteriaMenu2.append(('top 2000','2000')) - criteriaMenu2.append(('top 5000','5000')) - criteriaMenu2.append(('top 10000','10000')) - criteriaMenu2.append(('top 15000','15000')) - criteriaMenu2.append(('top 20000','20000')) - - criteriaMenu3 = HT.Select(name='criteria3', selected='500', onMouseOver="if (NS4 || IE4) activateEl('criterias', event);") - criteriaMenu3.append(('top 100','100')) - criteriaMenu3.append(('top 200','200')) - criteriaMenu3.append(('top 500','500')) - criteriaMenu3.append(('top 1000','1000')) - criteriaMenu3.append(('top 2000','2000')) - criteriaMenu3.append(('top 5000','5000')) - criteriaMenu3.append(('top 10000','10000')) - criteriaMenu3.append(('top 15000','15000')) - criteriaMenu3.append(('top 20000','20000')) - - - self.MDPRow1 = HT.TR(Class='mdp1') - self.MDPRow2 = HT.TR(Class='mdp2') - self.MDPRow3 = HT.TR(Class='mdp3') - - correlationMenus1 = HT.TableLite( - HT.TR(HT.TD(databaseText), HT.TD(databaseMenu1, colspan="3")), - HT.TR(HT.TD(criteriaText), HT.TD(criteriaMenu1)), - self.MDPRow1, cellspacing=0, width="619px", cellpadding=2) - correlationMenus1.append(HT.Input(name='orderBy', value='2', type='hidden')) # to replace the orderBy menu - correlationMenus2 = HT.TableLite( - HT.TR(HT.TD(databaseText), HT.TD(databaseMenu2, colspan="3")), - HT.TR(HT.TD(criteriaText), HT.TD(criteriaMenu2)), - self.MDPRow2, cellspacing=0, width="619px", cellpadding=2) - correlationMenus2.append(HT.Input(name='orderBy', value='2', type='hidden')) - correlationMenus3 = HT.TableLite( - HT.TR(HT.TD(databaseText), HT.TD(databaseMenu3, colspan="3")), - HT.TR(HT.TD(criteriaText), HT.TD(criteriaMenu3)), - self.MDPRow3, cellspacing=0, width="619px", cellpadding=2) - correlationMenus3.append(HT.Input(name='orderBy', value='2', type='hidden')) + tissue_id, tissue_name = item + #databaseMenuSub = HT.Optgroup(label = '%s ------' % tissue_name) + #dataset_sub_menu = [] + print("phun9") + self.cursor.execute('''SELECT ProbeSetFreeze.FullName,ProbeSetFreeze.Name FROM ProbeSetFreeze, ProbeFreeze, + InbredSet WHERE ProbeSetFreeze.ProbeFreezeId = ProbeFreeze.Id and ProbeFreeze.TissueId = %s and + ProbeSetFreeze.public > %s and ProbeFreeze.InbredSetId = InbredSet.Id and InbredSet.Name like %s + order by ProbeSetFreeze.CreateTime desc, ProbeSetFreeze.AvgId ''', + (tissue_id, webqtlConfig.PUBLICTHRESH, "%" + RISetgp + "%")) + print("phun8") + dataset_sub_menu = [item for item in self.cursor.fetchall() if item] + #for item2 in self.cursor.fetchall(): + # dataset_sub_menu.append(item2) + if dataset_sub_menu: + dataset_menu.append(dict(tissue=tissue_name, + datasets=dataset_sub_menu)) + # ("**heading**", tissue_name)) + #dataset_menu.append(dataset_sub_menu) + + dataset_menu_selected = None + if len(dataset_menu): + if thisTrait and thisTrait.db: + dataset_menu_selected = thisTrait.db.fullname - else: - correlationMenus = "" + #criteriaText = HT.Span("Return:", Class="ffl fwb fs12") + #criteriaMenu1 = HT.Select(name='criteria1', selected='500', onMouseOver="if (NS4 || IE4) activateEl('criterias', event);") + + return_results_menu = [] + + for counter in (100, 200, 500, 1000, 2000, 5000, 10000, 15000, 20000): + return_results_menu.append(('top %s' % (counter,), str(counter))) + + #criteriaMenu1.append(('top 100','100')) + #criteriaMenu1.append(('top 200','200')) + #criteriaMenu1.append(('top 500','500')) + #criteriaMenu1.append(('top 1000','1000')) + #criteriaMenu1.append(('top 2000','2000')) + #criteriaMenu1.append(('top 5000','5000')) + #criteriaMenu1.append(('top 10000','10000')) + #criteriaMenu1.append(('top 15000','15000')) + #criteriaMenu1.append(('top 20000','20000')) + + #self.MDPRow1 = HT.TR(Class='mdp1') + #self.MDPRow2 = HT.TR(Class='mdp2') + #self.MDPRow3 = HT.TR(Class='mdp3') + + # correlationMenus1 = HT.TableLite( + # HT.TR(HT.TD(databaseText), HT.TD(databaseMenu1, colspan="3")), + # HT.TR(HT.TD(criteriaText), HT.TD(criteriaMenu1)), + # self.MDPRow1, cellspacing=0, width="619px", cellpadding=2) + # correlationMenus1.append(HT.Input(name='orderBy', value='2', type='hidden')) # to replace the orderBy menu + # correlationMenus2 = HT.TableLite( + # HT.TR(HT.TD(databaseText), HT.TD(databaseMenu2, colspan="3")), + # HT.TR(HT.TD(criteriaText), HT.TD(criteriaMenu2)), + # self.MDPRow2, cellspacing=0, width="619px", cellpadding=2) + # correlationMenus2.append(HT.Input(name='orderBy', value='2', type='hidden')) + # correlationMenus3 = HT.TableLite( + # HT.TR(HT.TD(databaseText), HT.TD(databaseMenu3, colspan="3")), + # HT.TR(HT.TD(criteriaText), HT.TD(criteriaMenu3)), + # self.MDPRow3, cellspacing=0, width="619px", cellpadding=2) + # correlationMenus3.append(HT.Input(name='orderBy', value='2', type='hidden')) + # + #else: + # correlationMenus = "" - corr_row = HT.TR() - corr_container = HT.Div(id="corr_tabs", Class="ui-tabs") - if (thisTrait.db != None and thisTrait.db.type =='ProbeSet'): - corr_tab_list = [HT.Href(text='Sample r', url="#corrtabs-1"), HT.Href(text='Literature r', url="#corrtabs-2"), HT.Href(text='Tissue r', url="#corrtabs-3")] - else: - corr_tab_list = [HT.Href(text='Sample r', url="#corrtabs-1")] - - corr_tabs = HT.List(corr_tab_list) - corr_container.append(corr_tabs) - - if correlationMenus1 or correlationMenus2 or correlationMenus3: - sample_div = HT.Div(id="corrtabs-1") - sample_container = HT.Span() - - sample_type = HT.Input(type="radio", name="sample_method", value="1", checked="checked") - sample_type2 = HT.Input(type="radio", name="sample_method", value="2") - - sampleTable = HT.TableLite(cellspacing=0, cellpadding=0, width="100%") - sampleTD = HT.TD(correlationMenus1, HT.BR(), - "Pearson", sample_type, " "*3, "Spearman Rank", sample_type2, HT.BR(), HT.BR(), - sample_correlation, HT.BR(), HT.BR()) - - sampleTD.append(HT.Span("The ",HT.Href(url="/correlationAnnotation.html#sample_r", target="_blank", text="Sample Correlation")," is computed between trait data and", - " any ",HT.BR()," other traits in the sample database selected above. Use ", - HT.Href(url="/glossary.html#Correlations", target="_blank", text="Spearman Rank"), - HT.BR(),"when the sample size is small (<20) or when there are influential \ - outliers.", HT.BR(),Class="fs12")) - - sampleTable.append(sampleTD) - - sample_container.append(sampleTable) - sample_div.append(sample_container) - corr_container.append(sample_div) - - literature_div = HT.Div(id="corrtabs-2") - literature_container = HT.Span() - - literatureTable = HT.TableLite(cellspacing=0, cellpadding=0, width="100%") - literatureTD = HT.TD(correlationMenus2,HT.BR(),lit_correlation, HT.BR(), HT.BR()) - literatureTD.append(HT.Span("The ", HT.Href(url="/correlationAnnotation.html", target="_blank",text="Literature Correlation"), " (Lit r) between this gene and all other genes is computed",HT.BR(), - "using the ", HT.Href(url="https://grits.eecs.utk.edu/sgo/sgo.html", target="_blank", text="Semantic Gene Organizer"), - " and human, rat, and mouse data from PubMed. ", HT.BR(),"Values are ranked by Lit r, \ - but Sample r and Tissue r are also displayed.", HT.BR(), HT.BR(), - HT.Href(url="/glossary.html#Literature", target="_blank", text="More on using Lit r"), Class="fs12")) - literatureTable.append(literatureTD) - - literature_container.append(literatureTable) - literature_div.append(literature_container) - - if thisTrait.db != None: - if (thisTrait.db.type =='ProbeSet'): - corr_container.append(literature_div) - - tissue_div = HT.Div(id="corrtabs-3") - tissue_container = HT.Span() - - tissue_type = HT.Input(type="radio", name="tissue_method", value="4", checked="checked") - tissue_type2 = HT.Input(type="radio", name="tissue_method", value="5") - - tissueTable = HT.TableLite(cellspacing=0, cellpadding=0, width="100%") - tissueTD = HT.TD(correlationMenus3,HT.BR(), - "Pearson", tissue_type, " "*3, "Spearman Rank", tissue_type2, HT.BR(), HT.BR(), - tissue_correlation, HT.BR(), HT.BR()) - tissueTD.append(HT.Span("The ", HT.Href(url="/webqtl/main.py?FormID=tissueCorrelation", target="_blank", text="Tissue Correlation"), - " (Tissue r) estimates the similarity of expression of two genes",HT.BR()," or \ - transcripts across different cells, tissues, or organs (",HT.Href(url="/correlationAnnotation.html#tissue_r", target="_blank", text="glossary"),"). \ - Tissue correlations",HT.BR()," are generated by analyzing expression in multiple samples usually taken from \ - single cases.",HT.BR(),HT.Bold("Pearson")," and ",HT.Bold("Spearman Rank")," correlations have been computed for all pairs \ - of genes",HT.BR()," using data from mouse samples.", - HT.BR(), Class="fs12")) - tissueTable.append(tissueTD) - - tissue_container.append(tissueTable) - tissue_div.append(tissue_container) - if thisTrait.db != None: - if (thisTrait.db.type =='ProbeSet'): - corr_container.append(tissue_div) - - corr_row.append(HT.TD(corr_container)) - - corr_script = HT.Script(language="Javascript") - corr_script_text = """$(function() { $("#corr_tabs").tabs(); });""" - corr_script.append(corr_script_text) - - submitTable = HT.TableLite(cellspacing=0, cellpadding=0, width="100%", Class="target4") - submitTable.append(corr_row) - submitTable.append(corr_script) - - title3Body.append(submitTable) + #corr_row = HT.TR() + #corr_container = HT.Div(id="corr_tabs", Class="ui-tabs") + # + #if (thisTrait.db != None and thisTrait.db.type =='ProbeSet'): + # corr_tab_list = [HT.Href(text='Sample r', url="#corrtabs-1"), + # HT.Href(text='Literature r', url="#corrtabs-2"), + # HT.Href(text='Tissue r', url="#corrtabs-3")] + #else: + # corr_tab_list = [HT.Href(text='Sample r', url="#corrtabs-1")] + # + #corr_tabs = HT.List(corr_tab_list) + #corr_container.append(corr_tabs) + + #if correlationMenus1 or correlationMenus2 or correlationMenus3: + #sample_div = HT.Div(id="corrtabs-1") + #sample_container = HT.Span() + # + #sample_type = HT.Input(type="radio", name="sample_method", value="1", checked="checked") + #sample_type2 = HT.Input(type="radio", name="sample_method", value="2") + # + #sampleTable = HT.TableLite(cellspacing=0, cellpadding=0, width="100%") + #sampleTD = HT.TD(correlationMenus1, HT.BR(), + # "Pearson", sample_type, " "*3, "Spearman Rank", sample_type2, HT.BR(), HT.BR(), + # sample_correlation, HT.BR(), HT.BR()) + # + #sampleTD.append(HT.Span("The ", + # HT.Href(url="/correlationAnnotation.html#sample_r", target="_blank", + # text="Sample Correlation")," is computed between trait data and", + # " any ",HT.BR()," other traits in the sample database selected above. Use ", + # HT.Href(url="/glossary.html#Correlations", target="_blank", text="Spearman Rank"), + # HT.BR(),"when the sample size is small (<20) or when there are influential \ + # outliers.", HT.BR(),Class="fs12")) + + #sampleTable.append(sampleTD) + + #sample_container.append(sampleTable) + #sample_div.append(sample_container) + #corr_container.append(sample_div) + # + #literature_div = HT.Div(id="corrtabs-2") + #literature_container = HT.Span() + + #literatureTable = HT.TableLite(cellspacing=0, cellpadding=0, width="100%") + #literatureTD = HT.TD(correlationMenus2,HT.BR(),lit_correlation, HT.BR(), HT.BR()) + #literatureTD.append(HT.Span("The ", HT.Href(url="/correlationAnnotation.html", target="_blank",text="Literature Correlation"), " (Lit r) between this gene and all other genes is computed",HT.BR(), + # "using the ", HT.Href(url="https://grits.eecs.utk.edu/sgo/sgo.html", target="_blank", text="Semantic Gene Organizer"), + # " and human, rat, and mouse data from PubMed. ", HT.BR(),"Values are ranked by Lit r, \ + # but Sample r and Tissue r are also displayed.", HT.BR(), HT.BR(), + # HT.Href(url="/glossary.html#Literature", target="_blank", text="More on using Lit r"), Class="fs12")) + #literatureTable.append(literatureTD) + # + #literature_container.append(literatureTable) + #literature_div.append(literature_container) + # + #if thisTrait.db != None: + # if (thisTrait.db.type =='ProbeSet'): + # corr_container.append(literature_div) + # + #tissue_div = HT.Div(id="corrtabs-3") + #tissue_container = HT.Span() + # + #tissue_type = HT.Input(type="radio", name="tissue_method", value="4", checked="checked") + #tissue_type2 = HT.Input(type="radio", name="tissue_method", value="5") + # + #tissueTable = HT.TableLite(cellspacing=0, cellpadding=0, width="100%") + #tissueTD = HT.TD(correlationMenus3,HT.BR(), + # "Pearson", tissue_type, " "*3, "Spearman Rank", tissue_type2, HT.BR(), HT.BR(), + # tissue_correlation, HT.BR(), HT.BR()) + #tissueTD.append(HT.Span("The ", HT.Href(url="/webqtl/main.py?FormID=tissueCorrelation", target="_blank", text="Tissue Correlation"), + #" (Tissue r) estimates the similarity of expression of two genes",HT.BR()," or \ + #transcripts across different cells, tissues, or organs (",HT.Href(url="/correlationAnnotation.html#tissue_r", target="_blank", text="glossary"),"). \ + #Tissue correlations",HT.BR()," are generated by analyzing expression in multiple samples usually taken from \ + #single cases.",HT.BR(),HT.Bold("Pearson")," and ",HT.Bold("Spearman Rank")," correlations have been computed for all pairs \ + #of genes",HT.BR()," using data from mouse samples.", + #HT.BR(), Class="fs12")) + #tissueTable.append(tissueTD) + # + #tissue_container.append(tissueTable) + #tissue_div.append(tissue_container) + #if thisTrait.db != None: + # if (thisTrait.db.type =='ProbeSet'): + # corr_container.append(tissue_div) + # + #corr_row.append(HT.TD(corr_container)) + # + #corr_script = HT.Script(language="Javascript") + #corr_script_text = """$(function() { $("#corr_tabs").tabs(); });""" + #corr_script.append(corr_script_text) + # + #submitTable = HT.TableLite(cellspacing=0, cellpadding=0, width="100%", Class="target4") + #submitTable.append(corr_row) + #submitTable.append(corr_script) + # + #title3Body.append(submitTable) + self.correlation_tools = dict(dataset_menu = dataset_menu, + dataset_menu_selected = dataset_menu_selected, + return_results_menu = return_results_menu) def dispMappingTools(self, fd, title4Body, thisTrait): |