"""This class contains functions relating to trait data manipulation""" import os from functools import reduce from typing import Any, Dict, Union, Sequence import MySQLdb from gn3.settings import TMPDIR from gn3.random import random_string from gn3.function_helpers import compose from gn3.db.datasets import retrieve_trait_dataset def export_trait_data( trait_data: dict, samplelist: Sequence[str], dtype: str = "val", var_exists: bool = False, n_exists: bool = False): """ Export data according to `samplelist`. Mostly used in calculating correlations. DESCRIPTION: Migrated from https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/base/webqtlTrait.py#L166-L211 PARAMETERS trait: (dict) The dictionary of key-value pairs representing a trait samplelist: (list) A list of sample names dtype: (str) ... verify what this is ... var_exists: (bool) A flag indicating existence of variance n_exists: (bool) A flag indicating existence of ndata """ def __export_all_types(tdata, sample): sample_data = [] if tdata[sample]["value"]: sample_data.append(tdata[sample]["value"]) if var_exists: if tdata[sample]["variance"]: sample_data.append(tdata[sample]["variance"]) else: sample_data.append(None) if n_exists: if tdata[sample]["ndata"]: sample_data.append(tdata[sample]["ndata"]) else: sample_data.append(None) else: if var_exists and n_exists: sample_data += [None, None, None] elif var_exists or n_exists: sample_data += [None, None] else: sample_data.append(None) return tuple(sample_data) def __exporter(accumulator, sample): # pylint: disable=[R0911] if sample in trait_data["data"]: if dtype == "val": return accumulator + (trait_data["data"][sample]["value"], ) if dtype == "var": return accumulator + (trait_data["data"][sample]["variance"], ) if dtype == "N": return accumulator + (trait_data["data"][sample]["ndata"], ) if dtype == "all": return accumulator + __export_all_types(trait_data["data"], sample) raise KeyError("Type `%s` is incorrect" % dtype) if var_exists and n_exists: return accumulator + (None, None, None) if var_exists or n_exists: return accumulator + (None, None) return accumulator + (None,) return reduce(__exporter, samplelist, tuple()) def get_trait_csv_sample_data(conn: Any, trait_name: int, phenotype_id: int): """Fetch a trait and return it as a csv string""" def __float_strip(num_str): if str(num_str)[-2:] == ".0": return str(int(num_str)) return str(num_str) def __process_for_csv__(record): return ",".join([ __float_strip(record[key]) if record[key] is not None else "x" for key in ("sample_name", "value", "se_error", "nstrain")]) csv_data = ["Strain Name,Value,SE,Count"] + [ __process_for_csv__(record) for record in retrieve_publish_trait_data( {"trait_name": trait_name, "db": {"dataset_id": phenotype_id}}, conn)] return "\n".join(csv_data) def update_sample_data(conn: Any, #pylint: disable=[R0913] trait_name: str, strain_name: str, phenotype_id: int, value: Union[int, float, str], error: Union[int, float, str], count: Union[int, str]): """Given the right parameters, update sample-data from the relevant table.""" strain_id, data_id = "", "" with conn.cursor() as cursor: cursor.execute( ("SELECT Strain.Id, PublishData.Id FROM " "(PublishData, Strain, PublishXRef, PublishFreeze) " "LEFT JOIN PublishSE ON " "(PublishSE.DataId = PublishData.Id AND " "PublishSE.StrainId = PublishData.StrainId) " "LEFT JOIN NStrain ON " "(NStrain.DataId = PublishData.Id AND " "NStrain.StrainId = PublishData.StrainId) " "WHERE PublishXRef.InbredSetId = " "PublishFreeze.InbredSetId AND " "PublishData.Id = PublishXRef.DataId AND " "PublishXRef.Id = %s AND " "PublishXRef.PhenotypeId = %s " "AND PublishData.StrainId = Strain.Id " "AND Strain.Name = \"%s\"") % (trait_name, phenotype_id, str(strain_name))) strain_id, data_id = cursor.fetchone() updated_published_data: int = 0 updated_se_data: int = 0 updated_n_strains: int = 0 with conn.cursor() as cursor: # Update the PublishData table cursor.execute(("UPDATE PublishData SET value = %s " "WHERE StrainId = %s AND Id = %s"), (None if value == "x" else value, strain_id, data_id)) updated_published_data = cursor.rowcount # Update the PublishSE table cursor.execute(("UPDATE PublishSE SET error = %s " "WHERE StrainId = %s AND DataId = %s"), (None if error == "x" else error, strain_id, data_id)) updated_se_data = cursor.rowcount # Update the NStrain table cursor.execute(("UPDATE NStrain SET count = %s " "WHERE StrainId = %s AND DataId = %s"), (None if count == "x" else count, strain_id, data_id)) updated_n_strains = cursor.rowcount return (updated_published_data, updated_se_data, updated_n_strains) def delete_sample_data(conn: Any, trait_name: str, strain_name: str, phenotype_id: int): """Given the right parameters, delete sample-data from the relevant table.""" strain_id, data_id = "", "" deleted_published_data: int = 0 deleted_se_data: int = 0 deleted_n_strains: int = 0 with conn.cursor() as cursor: # Delete the PublishData table try: cursor.execute( ("SELECT Strain.Id, PublishData.Id FROM " "(PublishData, Strain, PublishXRef, PublishFreeze) " "LEFT JOIN PublishSE ON " "(PublishSE.DataId = PublishData.Id AND " "PublishSE.StrainId = PublishData.StrainId) " "LEFT JOIN NStrain ON " "(NStrain.DataId = PublishData.Id AND " "NStrain.StrainId = PublishData.StrainId) " "WHERE PublishXRef.InbredSetId = " "PublishFreeze.InbredSetId AND " "PublishData.Id = PublishXRef.DataId AND " "PublishXRef.Id = %s AND " "PublishXRef.PhenotypeId = %s " "AND PublishData.StrainId = Strain.Id " "AND Strain.Name = \"%s\"") % (trait_name, phenotype_id, str(strain_name))) # Check if it exists if the data was already deleted: if _result := cursor.fetchone(): strain_id, data_id = _result # Only run if the strain_id and data_id exist if strain_id and data_id: cursor.execute(("DELETE FROM PublishData " "WHERE StrainId = %s AND Id = %s") % (strain_id, data_id)) deleted_published_data = cursor.rowcount # Delete the PublishSE table cursor.execute(("DELETE FROM PublishSE " "WHERE StrainId = %s AND DataId = %s") % (strain_id, data_id)) deleted_se_data = cursor.rowcount # Delete the NStrain table cursor.execute(("DELETE FROM NStrain " "WHERE StrainId = %s AND DataId = %s" % (strain_id, data_id))) deleted_n_strains = cursor.rowcount except Exception as e: #pylint: disable=[C0103, W0612] conn.rollback() raise MySQLdb.Error conn.commit() cursor.close() cursor.close() return (deleted_published_data, deleted_se_data, deleted_n_strains) def insert_sample_data(conn: Any, #pylint: disable=[R0913] trait_name: str, strain_name: str, phenotype_id: int, value: Union[int, float, str], error: Union[int, float, str], count: Union[int, str]): """Given the right parameters, insert sample-data to the relevant table. """ inserted_published_data, inserted_se_data, inserted_n_strains = 0, 0, 0 with conn.cursor() as cursor: try: cursor.execute("SELECT DataId FROM PublishXRef WHERE Id = %s AND " "PhenotypeId = %s", (trait_name, phenotype_id)) data_id = cursor.fetchone() cursor.execute("SELECT Id FROM Strain WHERE Name = %s", (strain_name,)) strain_id = cursor.fetchone() # Return early if an insert already exists! cursor.execute("SELECT Id FROM PublishData where Id = %s " "AND StrainId = %s", (data_id, strain_id)) if cursor.fetchone(): # This strain already exists return (0, 0, 0) # Insert the PublishData table cursor.execute(("INSERT INTO PublishData (Id, StrainId, value)" "VALUES (%s, %s, %s)"), (data_id, strain_id, value)) inserted_published_data = cursor.rowcount # Insert into the PublishSE table if error is specified if error and error != "x": cursor.execute(("INSERT INTO PublishSE (StrainId, DataId, " " error) VALUES (%s, %s, %s)") % (strain_id, data_id, error)) inserted_se_data = cursor.rowcount # Insert into the NStrain table if count and count != "x": cursor.execute(("INSERT INTO NStrain " "(StrainId, DataId, error) " "VALUES (%s, %s, %s)") % (strain_id, data_id, count)) inserted_n_strains = cursor.rowcount except Exception as e: #pylint: disable=[C0103, W0612] conn.rollback() raise MySQLdb.Error return (inserted_published_data, inserted_se_data, inserted_n_strains) def retrieve_publish_trait_info(trait_data_source: Dict[str, Any], conn: Any): """Retrieve trait information for type `Publish` traits. https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/base/webqtlTrait.py#L399-L421""" keys = ( "Id", "PubMed_ID", "Pre_publication_description", "Post_publication_description", "Original_description", "Pre_publication_abbreviation", "Post_publication_abbreviation", "Lab_code", "Submitter", "Owner", "Authorized_Users", "Authors", "Title", "Abstract", "Journal", "Volume", "Pages", "Month", "Year", "Sequence", "Units", "comments") columns = ( "PublishXRef.Id, Publication.PubMed_ID, " "Phenotype.Pre_publication_description, " "Phenotype.Post_publication_description, " "Phenotype.Original_description, " "Phenotype.Pre_publication_abbreviation, " "Phenotype.Post_publication_abbreviation, " "Phenotype.Lab_code, Phenotype.Submitter, Phenotype.Owner, " "Phenotype.Authorized_Users, CAST(Publication.Authors AS BINARY), " "Publication.Title, Publication.Abstract, Publication.Journal, " "Publication.Volume, Publication.Pages, Publication.Month, " "Publication.Year, PublishXRef.Sequence, Phenotype.Units, " "PublishXRef.comments") query = ( "SELECT " "{columns} " "FROM " "PublishXRef, Publication, Phenotype " "WHERE " "PublishXRef.Id = %(trait_name)s AND " "Phenotype.Id = PublishXRef.PhenotypeId AND " "Publication.Id = PublishXRef.PublicationId AND " "PublishXRef.InbredSetId = %(trait_dataset_id)s").format(columns=columns) with conn.cursor() as cursor: cursor.execute( query, { k: v for k, v in trait_data_source.items() if k in ["trait_name", "trait_dataset_id"] }) return dict(zip([k.lower() for k in keys], cursor.fetchone())) def set_confidential_field(trait_type, trait_info): """Post processing function for 'Publish' trait types. It sets the value for the 'confidential' key.""" if trait_type == "Publish": return { **trait_info, "confidential": 1 if ( trait_info.get("pre_publication_description", None) and not trait_info.get("pubmed_id", None)) else 0} return trait_info def retrieve_probeset_trait_info(trait_data_source: Dict[str, Any], conn: Any): """Retrieve trait information for type `ProbeSet` traits. https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/base/webqtlTrait.py#L424-L435""" keys = ( "name", "symbol", "description", "probe_target_description", "chr", "mb", "alias", "geneid", "genbankid", "unigeneid", "omim", "refseq_transcriptid", "blatseq", "targetseq", "chipid", "comments", "strand_probe", "strand_gene", "probe_set_target_region", "proteinid", "probe_set_specificity", "probe_set_blat_score", "probe_set_blat_mb_start", "probe_set_blat_mb_end", "probe_set_strand", "probe_set_note_by_rw", "flag") query = ( "SELECT " "{columns} " "FROM " "ProbeSet, ProbeSetFreeze, ProbeSetXRef " "WHERE " "ProbeSetXRef.ProbeSetFreezeId = ProbeSetFreeze.Id AND " "ProbeSetXRef.ProbeSetId = ProbeSet.Id AND " "ProbeSetFreeze.Name = %(trait_dataset_name)s AND " "ProbeSet.Name = %(trait_name)s").format( columns=", ".join(["ProbeSet.{}".format(x) for x in keys])) with conn.cursor() as cursor: cursor.execute( query, { k: v for k, v in trait_data_source.items() if k in ["trait_name", "trait_dataset_name"] }) return dict(zip(keys, cursor.fetchone())) def retrieve_geno_trait_info(trait_data_source: Dict[str, Any], conn: Any): """Retrieve trait information for type `Geno` traits. https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/base/webqtlTrait.py#L438-L449""" keys = ("name", "chr", "mb", "source2", "sequence") query = ( "SELECT " "{columns} " "FROM " "Geno, GenoFreeze, GenoXRef " "WHERE " "GenoXRef.GenoFreezeId = GenoFreeze.Id AND GenoXRef.GenoId = Geno.Id AND " "GenoFreeze.Name = %(trait_dataset_name)s AND " "Geno.Name = %(trait_name)s").format( columns=", ".join(["Geno.{}".format(x) for x in keys])) with conn.cursor() as cursor: cursor.execute( query, { k: v for k, v in trait_data_source.items() if k in ["trait_name", "trait_dataset_name"] }) return dict(zip(keys, cursor.fetchone())) def retrieve_temp_trait_info(trait_data_source: Dict[str, Any], conn: Any): """Retrieve trait information for type `Temp` traits. https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/base/webqtlTrait.py#L450-452""" keys = ("name", "description") query = ( "SELECT {columns} FROM Temp " "WHERE Name = %(trait_name)s").format(columns=", ".join(keys)) with conn.cursor() as cursor: cursor.execute( query, { k: v for k, v in trait_data_source.items() if k in ["trait_name"] }) return dict(zip(keys, cursor.fetchone())) def set_haveinfo_field(trait_info): """ Common postprocessing function for all trait types. Sets the value for the 'haveinfo' field.""" return {**trait_info, "haveinfo": 1 if trait_info else 0} def set_homologene_id_field_probeset(trait_info, conn): """ Postprocessing function for 'ProbeSet' traits. Sets the value for the 'homologene' key. """ query = ( "SELECT HomologeneId FROM Homologene, Species, InbredSet" " WHERE Homologene.GeneId = %(geneid)s AND InbredSet.Name = %(group)s" " AND InbredSet.SpeciesId = Species.Id AND" " Species.TaxonomyId = Homologene.TaxonomyId") with conn.cursor() as cursor: cursor.execute( query, { k: v for k, v in trait_info.items() if k in ["geneid", "group"] }) res = cursor.fetchone() if res: return {**trait_info, "homologeneid": res[0]} return {**trait_info, "homologeneid": None} def set_homologene_id_field(trait_type, trait_info, conn): """ Common postprocessing function for all trait types. Sets the value for the 'homologene' key.""" def set_to_null(ti): return {**ti, "homologeneid": None} # pylint: disable=[C0103, C0321] functions_table = { "Temp": set_to_null, "Geno": set_to_null, "Publish": set_to_null, "ProbeSet": lambda ti: set_homologene_id_field_probeset(ti, conn) } return functions_table[trait_type](trait_info) def load_publish_qtl_info(trait_info, conn): """ Load extra QTL information for `Publish` traits """ query = ( "SELECT PublishXRef.Locus, PublishXRef.LRS, PublishXRef.additive " "FROM PublishXRef, PublishFreeze " "WHERE PublishXRef.Id = %(trait_name)s " "AND PublishXRef.InbredSetId = PublishFreeze.InbredSetId " "AND PublishFreeze.Id = %(dataset_id)s") with conn.cursor() as cursor: cursor.execute( query, { "trait_name": trait_info["trait_name"], "dataset_id": trait_info["db"]["dataset_id"] }) return dict(zip(["locus", "lrs", "additive"], cursor.fetchone())) return {"locus": "", "lrs": "", "additive": ""} def load_probeset_qtl_info(trait_info, conn): """ Load extra QTL information for `ProbeSet` traits """ query = ( "SELECT ProbeSetXRef.Locus, ProbeSetXRef.LRS, ProbeSetXRef.pValue, " "ProbeSetXRef.mean, ProbeSetXRef.additive " "FROM ProbeSetXRef, ProbeSet " "WHERE ProbeSetXRef.ProbeSetId = ProbeSet.Id " " AND ProbeSet.Name = %(trait_name)s " "AND ProbeSetXRef.ProbeSetFreezeId = %(dataset_id)s") with conn.cursor() as cursor: cursor.execute( query, { "trait_name": trait_info["trait_name"], "dataset_id": trait_info["db"]["dataset_id"] }) return dict(zip( ["locus", "lrs", "pvalue", "mean", "additive"], cursor.fetchone())) return {"locus": "", "lrs": "", "pvalue": "", "mean": "", "additive": ""} def load_qtl_info(qtl, trait_type, trait_info, conn): """ Load extra QTL information for traits DESCRIPTION: Migrated from https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/base/webqtlTrait.py#L500-L534 PARAMETERS: qtl: boolean trait_type: string The type of the trait in consideration trait_info: map/dictionary A dictionary of the trait's key-value pairs conn: A database connection object """ if not qtl: return trait_info qtl_info_functions = { "Publish": load_publish_qtl_info, "ProbeSet": load_probeset_qtl_info } if trait_info["name"] not in qtl_info_functions.keys(): return trait_info return qtl_info_functions[trait_type](trait_info, conn) def build_trait_name(trait_fullname): """ Initialises the trait's name, and other values from the search data provided """ def dataset_type(dset_name): if dset_name.find('Temp') >= 0: return "Temp" if dset_name.find('Geno') >= 0: return "Geno" if dset_name.find('Publish') >= 0: return "Publish" return "ProbeSet" name_parts = trait_fullname.split("::") assert len(name_parts) >= 2, f"Name format error: '{trait_fullname}'" dataset_name = name_parts[0] dataset_type = dataset_type(dataset_name) return { "db": { "dataset_name": dataset_name, "dataset_type": dataset_type}, "trait_fullname": trait_fullname, "trait_name": name_parts[1], "cellid": name_parts[2] if len(name_parts) == 3 else "" } def retrieve_probeset_sequence(trait, conn): """ Retrieve a 'ProbeSet' trait's sequence information """ query = ( "SELECT ProbeSet.BlatSeq " "FROM ProbeSet, ProbeSetFreeze, ProbeSetXRef " "WHERE ProbeSet.Id=ProbeSetXRef.ProbeSetId " "AND ProbeSetFreeze.Id = ProbeSetXRef.ProbeSetFreezeId " "AND ProbeSet.Name = %(trait_name)s " "AND ProbeSetFreeze.Name = %(dataset_name)s") with conn.cursor() as cursor: cursor.execute( query, { "trait_name": trait["trait_name"], "dataset_name": trait["db"]["dataset_name"] }) seq = cursor.fetchone() return {**trait, "sequence": seq[0] if seq else ""} def retrieve_trait_info( threshold: int, trait_full_name: str, conn: Any, qtl=None): """Retrieves the trait information. https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/base/webqtlTrait.py#L397-L456 This function, or the dependent functions, might be incomplete as they are currently.""" trait = build_trait_name(trait_full_name) trait_dataset_type = trait["db"]["dataset_type"] trait_info_function_table = { "Publish": retrieve_publish_trait_info, "ProbeSet": retrieve_probeset_trait_info, "Geno": retrieve_geno_trait_info, "Temp": retrieve_temp_trait_info } common_post_processing_fn = compose( lambda ti: load_qtl_info(qtl, trait_dataset_type, ti, conn), lambda ti: set_homologene_id_field(trait_dataset_type, ti, conn), lambda ti: {"trait_type": trait_dataset_type, **ti}, lambda ti: {**trait, **ti}) trait_post_processing_functions_table = { "Publish": compose( lambda ti: set_confidential_field(trait_dataset_type, ti), common_post_processing_fn), "ProbeSet": compose( lambda ti: retrieve_probeset_sequence(ti, conn), common_post_processing_fn), "Geno": common_post_processing_fn, "Temp": common_post_processing_fn } retrieve_info = compose( set_haveinfo_field, trait_info_function_table[trait_dataset_type]) trait_dataset = retrieve_trait_dataset( trait_dataset_type, trait, threshold, conn) trait_info = retrieve_info( { "trait_name": trait["trait_name"], "trait_dataset_id": trait_dataset["dataset_id"], "trait_dataset_name": trait_dataset["dataset_name"] }, conn) if trait_info["haveinfo"]: return { **trait_post_processing_functions_table[trait_dataset_type]( {**trait_info, "group": trait_dataset["group"]}), "db": {**trait["db"], **trait_dataset} } return trait_info def retrieve_temp_trait_data(trait_info: dict, conn: Any): """ Retrieve trait data for `Temp` traits. """ query = ( "SELECT " "Strain.Name, TempData.value, TempData.SE, TempData.NStrain, " "TempData.Id " "FROM TempData, Temp, Strain " "WHERE TempData.StrainId = Strain.Id " "AND TempData.Id = Temp.DataId " "AND Temp.name = %(trait_name)s " "ORDER BY Strain.Name") with conn.cursor() as cursor: cursor.execute( query, {"trait_name": trait_info["trait_name"]}) return [dict(zip( ["sample_name", "value", "se_error", "nstrain", "id"], row)) for row in cursor.fetchall()] return [] def retrieve_species_id(group, conn: Any): """ Retrieve a species id given the Group value """ with conn.cursor as cursor: cursor.execute( "SELECT SpeciesId from InbredSet WHERE Name = %(group)s", {"group": group}) return cursor.fetchone()[0] return None def retrieve_geno_trait_data(trait_info: Dict, conn: Any): """ Retrieve trait data for `Geno` traits. """ query = ( "SELECT Strain.Name, GenoData.value, GenoSE.error, GenoData.Id " "FROM (GenoData, GenoFreeze, Strain, Geno, GenoXRef) " "LEFT JOIN GenoSE ON " "(GenoSE.DataId = GenoData.Id AND GenoSE.StrainId = GenoData.StrainId) " "WHERE Geno.SpeciesId = %(species_id)s " "AND Geno.Name = %(trait_name)s AND GenoXRef.GenoId = Geno.Id " "AND GenoXRef.GenoFreezeId = GenoFreeze.Id " "AND GenoFreeze.Name = %(dataset_name)s " "AND GenoXRef.DataId = GenoData.Id " "AND GenoData.StrainId = Strain.Id " "ORDER BY Strain.Name") with conn.cursor() as cursor: cursor.execute( query, {"trait_name": trait_info["trait_name"], "dataset_name": trait_info["db"]["dataset_name"], "species_id": retrieve_species_id( trait_info["db"]["group"], conn)}) return [ dict(zip( ["sample_name", "value", "se_error", "id"], row)) for row in cursor.fetchall()] return [] def retrieve_publish_trait_data(trait_info: Dict, conn: Any): """ Retrieve trait data for `Publish` traits. """ query = ( "SELECT " "Strain.Name, PublishData.value, PublishSE.error, NStrain.count, " "PublishData.Id " "FROM (PublishData, Strain, PublishXRef) " "LEFT JOIN PublishSE ON " "(PublishSE.DataId = PublishData.Id " "AND PublishSE.StrainId = PublishData.StrainId) " "LEFT JOIN NStrain ON " "(NStrain.DataId = PublishData.Id " "AND NStrain.StrainId = PublishData.StrainId) " "WHERE PublishData.Id = PublishXRef.DataId " "AND PublishXRef.Id = %(trait_name)s " "AND PublishXRef.InbredSetId = %(dataset_id)s " "AND PublishData.StrainId = Strain.Id " "ORDER BY Strain.Name") with conn.cursor() as cursor: cursor.execute( query, {"trait_name": trait_info["trait_name"], "dataset_id": trait_info["db"]["dataset_id"]}) return [ dict(zip( ["sample_name", "value", "se_error", "nstrain", "id"], row)) for row in cursor.fetchall()] return [] def retrieve_cellid_trait_data(trait_info: Dict, conn: Any): """ Retrieve trait data for `Probe Data` types. """ query = ( "SELECT " "Strain.Name, ProbeData.value, ProbeSE.error, ProbeData.Id " "FROM (ProbeData, ProbeFreeze, ProbeSetFreeze, ProbeXRef, Strain," " Probe, ProbeSet) " "LEFT JOIN ProbeSE ON " "(ProbeSE.DataId = ProbeData.Id " " AND ProbeSE.StrainId = ProbeData.StrainId) " "WHERE Probe.Name = %(cellid)s " "AND ProbeSet.Name = %(trait_name)s " "AND Probe.ProbeSetId = ProbeSet.Id " "AND ProbeXRef.ProbeId = Probe.Id " "AND ProbeXRef.ProbeFreezeId = ProbeFreeze.Id " "AND ProbeSetFreeze.ProbeFreezeId = ProbeFreeze.Id " "AND ProbeSetFreeze.Name = %(dataset_name)s " "AND ProbeXRef.DataId = ProbeData.Id " "AND ProbeData.StrainId = Strain.Id " "ORDER BY Strain.Name") with conn.cursor() as cursor: cursor.execute( query, {"cellid": trait_info["cellid"], "trait_name": trait_info["trait_name"], "dataset_id": trait_info["db"]["dataset_id"]}) return [ dict(zip( ["sample_name", "value", "se_error", "id"], row)) for row in cursor.fetchall()] return [] def retrieve_probeset_trait_data(trait_info: Dict, conn: Any): """ Retrieve trait data for `ProbeSet` traits. """ query = ( "SELECT Strain.Name, ProbeSetData.value, ProbeSetSE.error, " "ProbeSetData.Id " "FROM (ProbeSetData, ProbeSetFreeze, Strain, ProbeSet, ProbeSetXRef) " "LEFT JOIN ProbeSetSE ON " "(ProbeSetSE.DataId = ProbeSetData.Id " "AND ProbeSetSE.StrainId = ProbeSetData.StrainId) " "WHERE ProbeSet.Name = %(trait_name)s " "AND ProbeSetXRef.ProbeSetId = ProbeSet.Id " "AND ProbeSetXRef.ProbeSetFreezeId = ProbeSetFreeze.Id " "AND ProbeSetFreeze.Name = %(dataset_name)s " "AND ProbeSetXRef.DataId = ProbeSetData.Id " "AND ProbeSetData.StrainId = Strain.Id " "ORDER BY Strain.Name") with conn.cursor() as cursor: cursor.execute( query, {"trait_name": trait_info["trait_name"], "dataset_name": trait_info["db"]["dataset_name"]}) return [ dict(zip( ["sample_name", "value", "se_error", "id"], row)) for row in cursor.fetchall()] return [] def with_samplelist_data_setup(samplelist: Sequence[str]): """ Build function that computes the trait data from provided list of samples. PARAMETERS samplelist: (list) A list of sample names RETURNS: Returns a function that given some data from the database, computes the sample's value, variance and ndata values, only if the sample is present in the provided `samplelist` variable. """ def setup_fn(tdata): if tdata["sample_name"] in samplelist: val = tdata["value"] if val is not None: return { "sample_name": tdata["sample_name"], "value": val, "variance": tdata["se_error"], "ndata": tdata.get("nstrain", None) } return None return setup_fn def without_samplelist_data_setup(): """ Build function that computes the trait data. RETURNS: Returns a function that given some data from the database, computes the sample's value, variance and ndata values. """ def setup_fn(tdata): val = tdata["value"] if val is not None: return { "sample_name": tdata["sample_name"], "value": val, "variance": tdata["se_error"], "ndata": tdata.get("nstrain", None) } return None return setup_fn def retrieve_trait_data(trait: dict, conn: Any, samplelist: Sequence[str] = tuple()): """ Retrieve trait data DESCRIPTION Retrieve trait data as is done in https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/base/webqtlTrait.py#L258-L386 """ # I do not like this section, but it retains the flow in the old codebase if trait["db"]["dataset_type"] == "Temp": results = retrieve_temp_trait_data(trait, conn) elif trait["db"]["dataset_type"] == "Publish": results = retrieve_publish_trait_data(trait, conn) elif trait["cellid"]: results = retrieve_cellid_trait_data(trait, conn) elif trait["db"]["dataset_type"] == "ProbeSet": results = retrieve_probeset_trait_data(trait, conn) else: results = retrieve_geno_trait_data(trait, conn) if results: # do something with mysqlid mysqlid = results[0]["id"] if samplelist: data = [ item for item in map(with_samplelist_data_setup(samplelist), results) if item is not None] else: data = [ item for item in map(without_samplelist_data_setup(), results) if item is not None] return { "mysqlid": mysqlid, "data": dict(map( lambda x: ( x["sample_name"], {k: v for k, v in x.items() if x != "sample_name"}), data))} return {} def generate_traits_filename(base_path: str = TMPDIR): """Generate a unique filename for use with generated traits files.""" return "{}/traits_test_file_{}.txt".format( os.path.abspath(base_path), random_string(10)) def export_informative(trait_data: dict, inc_var: bool = False) -> tuple: """ Export informative strain This is a migration of the `exportInformative` function in web/webqtl/base/webqtlTrait.py module in GeneNetwork1. There is a chance that the original implementation has a bug, especially dealing with the `inc_var` value. It the `inc_var` value is meant to control the inclusion of the `variance` value, then the current implementation, and that one in GN1 have a bug. """ def __exporter__(acc, data_item): if not inc_var or data_item["variance"] is not None: return ( acc[0] + (data_item["sample_name"],), acc[1] + (data_item["value"],), acc[2] + (data_item["variance"],)) return acc return reduce( __exporter__, filter(lambda td: td["value"] is not None, trait_data["data"].values()), (tuple(), tuple(), tuple()))