diff options
| -rw-r--r-- | wqflask/wqflask/do_search.py | 56 | ||||
| -rw-r--r-- | wqflask/wqflask/my_pylmm/pyLMM/lmm.py | 80 | ||||
| -rw-r--r-- | wqflask/wqflask/search_results.py | 30 | ||||
| -rw-r--r-- | wqflask/wqflask/static/new/javascript/marker_regression.coffee | 4 | ||||
| -rw-r--r-- | wqflask/wqflask/static/new/javascript/marker_regression.js | 4 | ||||
| -rw-r--r-- | wqflask/wqflask/templates/index_page.html | 4 |
6 files changed, 114 insertions, 64 deletions
diff --git a/wqflask/wqflask/do_search.py b/wqflask/wqflask/do_search.py index a2eddfc6..b390bdc4 100644 --- a/wqflask/wqflask/do_search.py +++ b/wqflask/wqflask/do_search.py @@ -20,17 +20,18 @@ class DoSearch(object): # Used to translate search phrases into classes search_types = dict() - def __init__(self, search_term, search_operator, dataset): + def __init__(self, search_term, search_operator=None, dataset=None): self.search_term = search_term # Make sure search_operator is something we expect assert search_operator in (None, "=", "<", ">", "<=", ">="), "Bad search operator" self.search_operator = search_operator self.dataset = dataset - print("self.dataset is boo: ", type(self.dataset), pf(self.dataset)) - print("self.dataset.group is: ", pf(self.dataset.group)) - - #Get group information for dataset and the species id - self.species_id = webqtlDatabaseFunction.retrieve_species_id(self.dataset.group.name) + + if self.dataset: + print("self.dataset is boo: ", type(self.dataset), pf(self.dataset)) + print("self.dataset.group is: ", pf(self.dataset.group)) + #Get group information for dataset and the species id + self.species_id = webqtlDatabaseFunction.retrieve_species_id(self.dataset.group.name) def execute(self, query): """Executes query and returns results""" @@ -59,6 +60,47 @@ class DoSearch(object): def get_search(cls, search_type): return cls.search_types[search_type] +class QuickMrnaAssaySearch(DoSearch): + """A general search for mRNA assays""" + + DoSearch.search_types['quick_mrna_assay'] = "QuickMrnaAssaySearch" + + base_query = """SELECT ProbeSet.Name as ProbeSet_Name, + ProbeSet.Chr_num as ProbeSet_Chr_Num, + ProbeSet.Mb as ProbeSet_Mb, + ProbeSet.Symbol as ProbeSet_Symbol, + ProbeSet.name_num as ProbeSet_name_num + FROM ProbeSet, + ProbeSetXRef, + ProbeSetFreeze, + ProbeFreeze, + InbredSet, + Species """ + + header_fields = ['', + 'Record ID', + 'Symbol', + 'Location'] + + def run(self): + """Generates and runs a search for assays across all mRNA expression datasets""" + + print("Running ProbeSetSearch") + query = self.base_query + """WHERE (MATCH (ProbeSet.Name, + ProbeSet.description, + ProbeSet.symbol) + AGAINST ('%s' IN BOOLEAN MODE)) and + ProbeSet.Id = ProbeSetXRef.ProbeSetId and + ProbeSetXRef.ProbeSetFreezeId = ProbeSetFreeze.Id and + ProbeSetFreeze.ProbeFreezeId = ProbeFreeze.Id and + ProbeFreeze.InbredSetId = InbredSet.Id and + InbredSet.SpeciesId = Species.Id + """ % (escape(self.search_term[0])) + + print("final query is:", pf(query)) + + return self.execute(query) + class MrnaAssaySearch(DoSearch): """A search within an mRNA expression dataset""" @@ -125,6 +167,8 @@ class MrnaAssaySearch(DoSearch): return self.execute(query) +#class QuickPhenotypeSearch(DoSearch): + class PhenotypeSearch(DoSearch): """A search within a phenotype dataset""" diff --git a/wqflask/wqflask/my_pylmm/pyLMM/lmm.py b/wqflask/wqflask/my_pylmm/pyLMM/lmm.py index 66830662..1e689e49 100644 --- a/wqflask/wqflask/my_pylmm/pyLMM/lmm.py +++ b/wqflask/wqflask/my_pylmm/pyLMM/lmm.py @@ -26,42 +26,42 @@ from scipy import stats from pprint import pformat as pf -#from utility.benchmark import Bench -# -##np.seterr('raise') -# -#def run(pheno_vector, -# genotype_matrix, -# restricted_max_likelihood=True, -# refit=False, -# temp_data=None): -# """Takes the phenotype vector and genotype matrix and returns a set of p-values and t-statistics -# -# restricted_max_likelihood -- whether to use restricted max likelihood; True or False -# refit -- whether to refit the variance component for each marker -# temp_data -- TempData object that stores the progress for each major step of the -# calculations ("calculate_kinship" and "GWAS" take the majority of time) -# -# """ -# -# with Bench("Calculate Kinship"): -# kinship_matrix = calculate_kinship(genotype_matrix, temp_data) -# -# with Bench("Create LMM object"): -# lmm_ob = LMM(pheno_vector, kinship_matrix) -# -# with Bench("LMM_ob fitting"): -# lmm_ob.fit() -# -# with Bench("Doing GWAS"): -# t_stats, p_values = GWAS(pheno_vector, -# genotype_matrix, -# kinship_matrix, -# restricted_max_likelihood=True, -# refit=False, -# temp_data=temp_data) -# Bench().report() -# return t_stats, p_values +from utility.benchmark import Bench + +#np.seterr('raise') + +def run(pheno_vector, + genotype_matrix, + restricted_max_likelihood=True, + refit=False, + temp_data=None): + """Takes the phenotype vector and genotype matrix and returns a set of p-values and t-statistics + + restricted_max_likelihood -- whether to use restricted max likelihood; True or False + refit -- whether to refit the variance component for each marker + temp_data -- TempData object that stores the progress for each major step of the + calculations ("calculate_kinship" and "GWAS" take the majority of time) + + """ + + with Bench("Calculate Kinship"): + kinship_matrix = calculate_kinship(genotype_matrix, temp_data) + + with Bench("Create LMM object"): + lmm_ob = LMM(pheno_vector, kinship_matrix) + + with Bench("LMM_ob fitting"): + lmm_ob.fit() + + with Bench("Doing GWAS"): + t_stats, p_values = GWAS(pheno_vector, + genotype_matrix, + kinship_matrix, + restricted_max_likelihood=True, + refit=False, + temp_data=temp_data) + Bench().report() + return t_stats, p_values def matrixMult(A,B): @@ -99,8 +99,8 @@ def calculate_kinship(genotype_matrix, temp_data): """ n = genotype_matrix.shape[0] m = genotype_matrix.shape[1] - print("n is:", n) - print("m is:", m) + #print("n is:", n) + #print("m is:", m) keep = [] for counter in range(m): print("type of genotype_matrix[:,counter]:", pf(genotype_matrix[:,counter])) @@ -123,7 +123,6 @@ def calculate_kinship(genotype_matrix, temp_data): genotype_matrix[:,counter] = (genotype_matrix[:,counter] - values_mean) / np.sqrt(vr) percent_complete = int(round((counter/m)*45)) - print("Percent complete: ", percent_complete) temp_data.store("percent_complete", percent_complete) genotype_matrix = genotype_matrix[:,keep] @@ -220,7 +219,6 @@ def GWAS(pheno_vector, ts, ps = lmm_ob.association(x, REML=restricted_max_likelihood) percent_complete = 45 + int(round((counter/m)*55)) - print("Percent complete: ", percent_complete) temp_data.store("percent_complete", percent_complete) p_values.append(ps) @@ -279,6 +277,8 @@ class LMM: self.K = K self.Kva = Kva self.Kve = Kve + print("self.Kva is: ", pf(self.Kva)) + print("self.Kve is: ", pf(self.Kve)) self.Y = Y self.X0 = X0 self.N = self.K.shape[0] diff --git a/wqflask/wqflask/search_results.py b/wqflask/wqflask/search_results.py index 080568f0..2d39a711 100644 --- a/wqflask/wqflask/search_results.py +++ b/wqflask/wqflask/search_results.py @@ -45,7 +45,7 @@ class SearchResultPage(): ########################################### # Names and IDs of group / F2 set ########################################### - + # All Phenotypes is a special case we'll deal with later #if kw['dataset'] == "All Phenotypes": # self.cursor.execute(""" @@ -57,15 +57,16 @@ class SearchResultPage(): # self.dataset_groups = map(lambda x: x[1], results) # self.dataset_group_ids = map(lambda x: x[2], results) #else: - + self.results = [] - + if 'q' in kw: - self.quick_search = True + #self.quick_search = True self.search_terms = kw['q'] + print("self.search_terms is: ", self.search_terms) self.quick_search() else: - self.quick_search = False + #self.quick_search = False self.search_terms = kw['search_terms'] self.dataset = create_dataset(kw['dataset']) self.search() @@ -98,10 +99,23 @@ class SearchResultPage(): self.trait_list.append(this_trait) self.dataset.get_trait_info(self.trait_list, species) - + def quick_search(self): + self.search_terms = parser.parse(self.search_terms) + print("After parsing:", self.search_terms) - return True + for a_search in self.search_terms: + search_term = a_search['search_term'] + #Do mRNA assay search + search_ob = do_search.DoSearch.get_search("quick_mrna_assay") + search_class = getattr(do_search, search_ob) + the_search = search_class(search_term) + + self.results.extend(the_search.run()) + print("in the search results are:", self.results) + + + #return True #search_gene #search_geno @@ -114,8 +128,6 @@ class SearchResultPage(): self.search_terms = parser.parse(self.search_terms) print("After parsing:", self.search_terms) - - for a_search in self.search_terms: print("[kodak] item is:", pf(a_search)) search_term = a_search['search_term'] diff --git a/wqflask/wqflask/static/new/javascript/marker_regression.coffee b/wqflask/wqflask/static/new/javascript/marker_regression.coffee index 4d678bde..6e605fa7 100644 --- a/wqflask/wqflask/static/new/javascript/marker_regression.coffee +++ b/wqflask/wqflask/static/new/javascript/marker_regression.coffee @@ -85,7 +85,7 @@ $ -> marker_name = marker_info[2] else marker_name = "" - $("#qtl_results_filter").find("input:first").val(marker_name).keyup() + $("#qtl_results_filter").find("input:first").val(marker_name).keypress() create_svg: () -> svg = d3.select("#manhattan_plots") @@ -279,8 +279,6 @@ $ -> ) .classed("circle", true) .on("mouseover", (d) => - console.log("foodie") - console.log("this:", this) console.log("d3.event is:", d3.event) console.log("d is:", d) this_id = "point_" + String(d[2]) diff --git a/wqflask/wqflask/static/new/javascript/marker_regression.js b/wqflask/wqflask/static/new/javascript/marker_regression.js index f5bb0c41..cb3c09cb 100644 --- a/wqflask/wqflask/static/new/javascript/marker_regression.js +++ b/wqflask/wqflask/static/new/javascript/marker_regression.js @@ -103,7 +103,7 @@ } else { marker_name = ""; } - return $("#qtl_results_filter").find("input:first").val(marker_name).keyup(); + return $("#qtl_results_filter").find("input:first").val(marker_name).keypress(); }; Manhattan_Plot.prototype.create_svg = function() { @@ -252,8 +252,6 @@ return "point_" + String(d[2]); }).classed("circle", true).on("mouseover", function(d) { var this_id; - console.log("foodie"); - console.log("this:", _this); console.log("d3.event is:", d3.event); console.log("d is:", d); this_id = "point_" + String(d[2]); diff --git a/wqflask/wqflask/templates/index_page.html b/wqflask/wqflask/templates/index_page.html index 46a307b7..09172705 100644 --- a/wqflask/wqflask/templates/index_page.html +++ b/wqflask/wqflask/templates/index_page.html @@ -8,12 +8,10 @@ <header class="jumbotron subhead" id="overview"> <div class="container"> <h1>GeneNetwork</h1> - <p class="lead">Open source bioinformatics for systems genetics<br /> - Brought to you by the University of Tennessee</p> + <p class="lead">Open source bioinformatics for systems genetics</p> </div> </header> - <div class="container"> <div class="row"> <div class="span3 bs-docs-sidebar"> |