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-rw-r--r--gn3/computations/partial_correlations.py2
-rw-r--r--gn3/db/partial_correlations.py826
2 files changed, 827 insertions, 1 deletions
diff --git a/gn3/computations/partial_correlations.py b/gn3/computations/partial_correlations.py
index 984c15a..0d4394b 100644
--- a/gn3/computations/partial_correlations.py
+++ b/gn3/computations/partial_correlations.py
@@ -539,7 +539,7 @@ def trait_for_output(trait):
pair just to indicate it does not exist.
"""
trait = {
- "trait_type": trait["trait_type"],
+ "trait_type": trait["db"]["dataset_type"],
"dataset_name": trait["db"]["dataset_name"],
"dataset_type": trait["db"]["dataset_type"],
"group": trait["db"]["group"],
diff --git a/gn3/db/partial_correlations.py b/gn3/db/partial_correlations.py
new file mode 100644
index 0000000..9a4d814
--- /dev/null
+++ b/gn3/db/partial_correlations.py
@@ -0,0 +1,826 @@
+"""
+This module contains the code and queries for fetching data from the database,
+that relates to partial correlations.
+
+It is intended to replace the functions in `gn3.db.traits` and `gn3.db.datasets`
+modules with functions that fetch the data enmasse, rather than one at a time.
+
+This module is part of the optimisation effort for the partial correlations.
+"""
+
+from functools import reduce, partial
+from typing import Any, Dict, Tuple, Union, Sequence
+
+from MySQLdb.cursors import DictCursor
+
+from gn3.function_helpers import compose
+from gn3.db.traits import (
+ build_trait_name,
+ with_samplelist_data_setup,
+ without_samplelist_data_setup)
+
+def organise_trait_data_by_trait(
+ traits_data_rows: Tuple[Dict[str, Any], ...]) -> Dict[
+ str, Dict[str, Any]]:
+ """
+ Organise the trait data items by their trait names.
+ """
+ def __organise__(acc, row):
+ trait_name = row["trait_name"]
+ return {
+ **acc,
+ trait_name: acc.get(trait_name, tuple()) + ({
+ key: val for key, val in row.items() if key != "trait_name"},)
+ }
+ if traits_data_rows:
+ return reduce(__organise__, traits_data_rows, {})
+ return {}
+
+def temp_traits_data(conn, traits):
+ """
+ Retrieve trait data for `Temp` traits.
+ """
+ query = (
+ "SELECT "
+ "Temp.Name AS trait_name, Strain.Name AS sample_name, TempData.value, "
+ "TempData.SE AS se_error, TempData.NStrain AS nstrain, "
+ "TempData.Id AS id "
+ "FROM TempData, Temp, Strain "
+ "WHERE TempData.StrainId = Strain.Id "
+ "AND TempData.Id = Temp.DataId "
+ "AND Temp.name IN ({}) "
+ "ORDER BY Strain.Name").format(
+ ", ".join(["%s"] * len(traits)))
+ with conn.cursor(cursorclass=DictCursor) as cursor:
+ cursor.execute(
+ query,
+ tuple(trait["trait_name"] for trait in traits))
+ return organise_trait_data_by_trait(cursor.fetchall())
+ return {}
+
+def publish_traits_data(conn, traits):
+ """
+ Retrieve trait data for `Publish` traits.
+ """
+ dataset_ids = tuple(set(trait["db"]["dataset_id"] for trait in traits))
+ query = (
+ "SELECT "
+ "PublishXRef.Id AS trait_name, Strain.Name AS sample_name, "
+ "PublishData.value, PublishSE.error AS se_error, "
+ "NStrain.count AS nstrain, PublishData.Id AS 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 IN ({trait_names}) "
+ "AND PublishFreeze.Id IN ({dataset_ids}) "
+ "AND PublishData.StrainId = Strain.Id "
+ "ORDER BY Strain.Name").format(
+ trait_names=", ".join(["%s"] * len(traits)),
+ dataset_ids=", ".join(["%s"] * len(dataset_ids)))
+ with conn.cursor(cursorclass=DictCursor) as cursor:
+ cursor.execute(
+ query,
+ tuple(trait["trait_name"] for trait in traits) +
+ tuple(dataset_ids))
+ return organise_trait_data_by_trait(cursor.fetchall())
+ return {}
+
+def cellid_traits_data(conn, traits):
+ """
+ Retrieve trait data for `Probe Data` types.
+ """
+ cellids = tuple(trait["cellid"] for trait in traits)
+ dataset_names = set(trait["db"]["dataset_name"] for trait in traits)
+ query = (
+ "SELECT "
+ "ProbeSet.Name AS trait_name, Strain.Name AS sample_name, "
+ "ProbeData.value, ProbeSE.error AS se_error, ProbeData.Id AS 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 IN ({cellids}) "
+ "AND ProbeSet.Name IN ({trait_names}) "
+ "AND Probe.ProbeSetId = ProbeSet.Id "
+ "AND ProbeXRef.ProbeId = Probe.Id "
+ "AND ProbeXRef.ProbeFreezeId = ProbeFreeze.Id "
+ "AND ProbeSetFreeze.ProbeFreezeId = ProbeFreeze.Id "
+ "AND ProbeSetFreeze.Name IN ({dataset_names}) "
+ "AND ProbeXRef.DataId = ProbeData.Id "
+ "AND ProbeData.StrainId = Strain.Id "
+ "ORDER BY Strain.Name").format(
+ cellids=", ".join(["%s"] * len(cellids)),
+ trait_names=", ".join(["%s"] * len(traits)),
+ dataset_names=", ".join(["%s"] * len(dataset_names)))
+ with conn.cursor(cursorclass=DictCursor) as cursor:
+ cursor.execute(
+ query,
+ cellids + tuple(trait["trait_name"] for trait in traits) +
+ tuple(dataset_names))
+ return organise_trait_data_by_trait(cursor.fetchall())
+ return {}
+
+def probeset_traits_data(conn, traits):
+ """
+ Retrieve trait data for `ProbeSet` traits.
+ """
+ dataset_names = set(trait["db"]["dataset_name"] for trait in traits)
+ query = (
+ "SELECT ProbeSet.Name AS trait_name, Strain.Name AS sample_name, "
+ "ProbeSetData.value, ProbeSetSE.error AS se_error, "
+ "ProbeSetData.Id AS id "
+ "FROM (ProbeSetData, ProbeSetFreeze, Strain, ProbeSet, ProbeSetXRef) "
+ "LEFT JOIN ProbeSetSE ON "
+ "(ProbeSetSE.DataId = ProbeSetData.Id "
+ "AND ProbeSetSE.StrainId = ProbeSetData.StrainId) "
+ "WHERE ProbeSet.Name IN ({trait_names}) "
+ "AND ProbeSetXRef.ProbeSetId = ProbeSet.Id "
+ "AND ProbeSetXRef.ProbeSetFreezeId = ProbeSetFreeze.Id "
+ "AND ProbeSetFreeze.Name IN ({dataset_names}) "
+ "AND ProbeSetXRef.DataId = ProbeSetData.Id "
+ "AND ProbeSetData.StrainId = Strain.Id "
+ "ORDER BY Strain.Name").format(
+ trait_names=", ".join(["%s"] * len(traits)),
+ dataset_names=", ".join(["%s"] * len(dataset_names)))
+ with conn.cursor(cursorclass=DictCursor) as cursor:
+ cursor.execute(
+ query,
+ tuple(trait["trait_name"] for trait in traits) +
+ tuple(dataset_names))
+ return organise_trait_data_by_trait(cursor.fetchall())
+ return {}
+
+def species_ids(conn, traits):
+ """
+ Retrieve the IDS of the related species from the given list of traits.
+ """
+ groups = tuple(set(trait["db"]["group"] for trait in traits))
+ query = (
+ "SELECT Name AS `group`, SpeciesId AS species_id "
+ "FROM InbredSet "
+ "WHERE Name IN ({groups})").format(
+ groups=", ".join(["%s"] * len(groups)))
+ with conn.cursor(cursorclass=DictCursor) as cursor:
+ cursor.execute(query, groups)
+ return tuple(row for row in cursor.fetchall())
+ return tuple()
+
+def geno_traits_data(conn, traits):
+ """
+ Retrieve trait data for `Geno` traits.
+ """
+ sp_ids = tuple(item["species_id"] for item in species_ids(conn, traits))
+ dataset_names = set(trait["db"]["dataset_name"] for trait in traits)
+ query = (
+ "SELECT Geno.Name AS trait_name, Strain.Name AS sample_name, "
+ "GenoData.value, GenoSE.error AS se_error, GenoData.Id AS id "
+ "FROM (GenoData, GenoFreeze, Strain, Geno, GenoXRef) "
+ "LEFT JOIN GenoSE ON "
+ "(GenoSE.DataId = GenoData.Id AND GenoSE.StrainId = GenoData.StrainId) "
+ "WHERE Geno.SpeciesId IN ({species_ids}) "
+ "AND Geno.Name IN ({trait_names}) AND GenoXRef.GenoId = Geno.Id "
+ "AND GenoXRef.GenoFreezeId = GenoFreeze.Id "
+ "AND GenoFreeze.Name IN ({dataset_names}) "
+ "AND GenoXRef.DataId = GenoData.Id "
+ "AND GenoData.StrainId = Strain.Id "
+ "ORDER BY Strain.Name").format(
+ species_ids=sp_ids,
+ trait_names=", ".join(["%s"] * len(traits)),
+ dataset_names=", ".join(["%s"] * len(dataset_names)))
+ with conn.cursor(cursorclass=DictCursor) as cursor:
+ cursor.execute(
+ query,
+ tuple(trait["trait_name"] for trait in traits) +
+ tuple(dataset_names))
+ return organise_trait_data_by_trait(cursor.fetchall())
+ return {}
+
+def traits_data(
+ conn: Any, traits: Tuple[Dict[str, Any], ...],
+ samplelist: Tuple[str, ...] = tuple()) -> Dict[str, Dict[str, Any]]:
+ """
+ Retrieve trait data for multiple `traits`
+
+ This is a rework of the `gn3.db.traits.retrieve_trait_data` function.
+ """
+ def __organise__(acc, trait):
+ dataset_type = trait["db"]["dataset_type"]
+ if dataset_type == "Temp":
+ return {**acc, "Temp": acc.get("Temp", tuple()) + (trait,)}
+ if dataset_type == "Publish":
+ return {**acc, "Publish": acc.get("Publish", tuple()) + (trait,)}
+ if trait.get("cellid"):
+ return {**acc, "cellid": acc.get("cellid", tuple()) + (trait,)}
+ if dataset_type == "ProbeSet":
+ return {**acc, "ProbeSet": acc.get("ProbeSet", tuple()) + (trait,)}
+ return {**acc, "Geno": acc.get("Geno", tuple()) + (trait,)}
+
+ def __setup_samplelist__(data):
+ if samplelist:
+ return tuple(
+ item for item in
+ map(with_samplelist_data_setup(samplelist), data)
+ if item is not None)
+ return tuple(
+ item for item in
+ map(without_samplelist_data_setup(), data)
+ if item is not None)
+
+ def __process_results__(results):
+ flattened = reduce(lambda acc, res: {**acc, **res}, results)
+ return {
+ trait_name: {"data": dict(map(
+ lambda item: (
+ item["sample_name"],
+ {
+ key: val for key, val in item.items()
+ if item != "sample_name"
+ }),
+ __setup_samplelist__(data)))}
+ for trait_name, data in flattened.items()}
+
+ traits_data_fns = {
+ "Temp": temp_traits_data,
+ "Publish": publish_traits_data,
+ "cellid": cellid_traits_data,
+ "ProbeSet": probeset_traits_data,
+ "Geno": geno_traits_data
+ }
+ return __process_results__(tuple(# type: ignore[var-annotated]
+ traits_data_fns[key](conn, vals)
+ for key, vals in reduce(__organise__, traits, {}).items()))
+
+def merge_traits_and_info(traits, info_results):
+ """
+ Utility to merge trait info retrieved from the database with the given traits.
+ """
+ if info_results:
+ results = {
+ trait["trait_name"]: trait for trait in info_results
+ }
+ return tuple(
+ {
+ **trait,
+ **results.get(trait["trait_name"], {}),
+ "haveinfo": bool(results.get(trait["trait_name"]))
+ } for trait in traits)
+ return tuple({**trait, "haveinfo": False} for trait in traits)
+
+def publish_traits_info(
+ conn: Any, traits: Tuple[Dict[str, Any], ...]) -> Tuple[
+ Dict[str, Any], ...]:
+ """
+ Retrieve trait information for type `Publish` traits.
+
+ This is a rework of `gn3.db.traits.retrieve_publish_trait_info` function:
+ this one fetches multiple items in a single query, unlike the original that
+ fetches one item per query.
+ """
+ trait_dataset_ids = set(trait["db"]["dataset_id"] for trait in traits)
+ 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) AS Authors, Publication.Title, "
+ "Publication.Abstract, Publication.Journal, Publication.Volume, "
+ "Publication.Pages, Publication.Month, Publication.Year, "
+ "PublishXRef.Sequence, Phenotype.Units, PublishXRef.comments")
+ query = (
+ "SELECT "
+ "PublishXRef.Id AS trait_name, {columns} "
+ "FROM "
+ "PublishXRef, Publication, Phenotype, PublishFreeze "
+ "WHERE "
+ "PublishXRef.Id IN ({trait_names}) "
+ "AND Phenotype.Id = PublishXRef.PhenotypeId "
+ "AND Publication.Id = PublishXRef.PublicationId "
+ "AND PublishXRef.InbredSetId = PublishFreeze.InbredSetId "
+ "AND PublishFreeze.Id IN ({trait_dataset_ids})").format(
+ columns=columns,
+ trait_names=", ".join(["%s"] * len(traits)),
+ trait_dataset_ids=", ".join(["%s"] * len(trait_dataset_ids)))
+ with conn.cursor(cursorclass=DictCursor) as cursor:
+ cursor.execute(
+ query,
+ tuple(trait["trait_name"] for trait in traits) +
+ tuple(trait_dataset_ids))
+ return merge_traits_and_info(traits, cursor.fetchall())
+ return tuple({**trait, "haveinfo": False} for trait in traits)
+
+def probeset_traits_info(
+ conn: Any, traits: Tuple[Dict[str, Any], ...]):
+ """
+ Retrieve information for the probeset traits
+ """
+ dataset_names = set(trait["db"]["dataset_name"] for trait in traits)
+ 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 ProbeSet.Name AS trait_name, {columns} "
+ "FROM ProbeSet, ProbeSetFreeze, ProbeSetXRef "
+ "WHERE ProbeSetXRef.ProbeSetFreezeId = ProbeSetFreeze.Id "
+ "AND ProbeSetXRef.ProbeSetId = ProbeSet.Id "
+ "AND ProbeSetFreeze.Name IN ({dataset_names}) "
+ "AND ProbeSet.Name IN ({trait_names})").format(
+ columns=", ".join(["ProbeSet.{}".format(x) for x in keys]),
+ dataset_names=", ".join(["%s"] * len(dataset_names)),
+ trait_names=", ".join(["%s"] * len(traits)))
+ with conn.cursor(cursorclass=DictCursor) as cursor:
+ cursor.execute(
+ query,
+ tuple(dataset_names) + tuple(
+ trait["trait_name"] for trait in traits))
+ return merge_traits_and_info(traits, cursor.fetchall())
+ return tuple({**trait, "haveinfo": False} for trait in traits)
+
+def geno_traits_info(
+ conn: Any, traits: Tuple[Dict[str, Any], ...]):
+ """
+ Retrieve trait information for type `Geno` traits.
+
+ This is a rework of the `gn3.db.traits.retrieve_geno_trait_info` function.
+ """
+ dataset_names = set(trait["db"]["dataset_name"] for trait in traits)
+ keys = ("name", "chr", "mb", "source2", "sequence")
+ query = (
+ "SELECT "
+ "Geno.Name AS trait_name, {columns} "
+ "FROM "
+ "Geno, GenoFreeze, GenoXRef "
+ "WHERE "
+ "GenoXRef.GenoFreezeId = GenoFreeze.Id AND GenoXRef.GenoId = Geno.Id AND "
+ "GenoFreeze.Name IN ({dataset_names}) AND "
+ "Geno.Name IN ({trait_names})").format(
+ columns=", ".join(["Geno.{}".format(x) for x in keys]),
+ dataset_names=", ".join(["%s"] * len(dataset_names)),
+ trait_names=", ".join(["%s"] * len(traits)))
+ with conn.cursor(cursorclass=DictCursor) as cursor:
+ cursor.execute(
+ query,
+ tuple(dataset_names) + tuple(
+ trait["trait_name"] for trait in traits))
+ return merge_traits_and_info(traits, cursor.fetchall())
+ return tuple({**trait, "haveinfo": False} for trait in traits)
+
+def temp_traits_info(
+ conn: Any, traits: Tuple[Dict[str, Any], ...]):
+ """
+ Retrieve trait information for type `Temp` traits.
+
+ A rework of the `gn3.db.traits.retrieve_temp_trait_info` function.
+ """
+ keys = ("name", "description")
+ query = (
+ "SELECT Name as trait_name, {columns} FROM Temp "
+ "WHERE Name = ({trait_names})").format(
+ columns=", ".join(keys),
+ trait_names=", ".join(["%s"] * len(traits)))
+ with conn.cursor(cursorclass=DictCursor) as cursor:
+ cursor.execute(
+ query,
+ tuple(trait["trait_name"] for trait in traits))
+ return merge_traits_and_info(traits, cursor.fetchall())
+ return tuple({**trait, "haveinfo": False} for trait in traits)
+
+def publish_datasets_names(
+ conn: Any, threshold: int, dataset_names: Tuple[str, ...]):
+ """
+ Get the ID, DataScale and various name formats for a `Publish` trait.
+
+ Rework of the `gn3.db.datasets.retrieve_publish_trait_dataset_name`
+ """
+ query = (
+ "SELECT DISTINCT "
+ "Id AS dataset_id, Name AS dataset_name, FullName AS dataset_fullname, "
+ "ShortName AS dataset_shortname "
+ "FROM PublishFreeze "
+ "WHERE "
+ "public > %s "
+ "AND "
+ "(Name IN ({names}) OR FullName IN ({names}) OR ShortName IN ({names}))")
+ with conn.cursor(cursorclass=DictCursor) as cursor:
+ cursor.execute(
+ query.format(names=", ".join(["%s"] * len(dataset_names))),
+ (threshold,) +(dataset_names * 3))
+ return {ds["dataset_name"]: ds for ds in cursor.fetchall()}
+ return {}
+
+def set_bxd(group_info):
+ """Set the group value to BXD if it is 'BXD300'."""
+ return {
+ **group_info,
+ "group": (
+ "BXD" if group_info.get("Name") == "BXD300"
+ else group_info.get("Name", "")),
+ "groupid": group_info["Id"]
+ }
+
+def organise_groups_by_dataset(
+ group_rows: Union[Sequence[Dict[str, Any]], None]) -> Dict[str, Any]:
+ """Utility: Organise given groups by their datasets."""
+ if group_rows:
+ return {
+ row["dataset_name"]: set_bxd({
+ key: val for key, val in row.items()
+ if key != "dataset_name"
+ }) for row in group_rows
+ }
+ return {}
+
+def publish_datasets_groups(conn: Any, dataset_names: Tuple[str]):
+ """
+ Retrieve the Group, and GroupID values for various Publish trait types.
+
+ Rework of `gn3.db.datasets.retrieve_publish_group_fields` function.
+ """
+ query = (
+ "SELECT PublishFreeze.Name AS dataset_name, InbredSet.Name, "
+ "InbredSet.Id "
+ "FROM InbredSet, PublishFreeze "
+ "WHERE PublishFreeze.InbredSetId = InbredSet.Id "
+ "AND PublishFreeze.Name IN ({dataset_names})").format(
+ dataset_names=", ".join(["%s"] * len(dataset_names)))
+ with conn.cursor(cursorclass=DictCursor) as cursor:
+ cursor.execute(query, tuple(dataset_names))
+ return organise_groups_by_dataset(cursor.fetchall())
+ return {}
+
+def publish_traits_datasets(conn: Any, threshold, traits: Tuple[Dict]):
+ """Retrieve datasets for 'Publish' traits."""
+ dataset_names = tuple(set(trait["db"]["dataset_name"] for trait in traits))
+ dataset_names_info = publish_datasets_names(conn, threshold, dataset_names)
+ dataset_groups = publish_datasets_groups(conn, dataset_names) # type: ignore[arg-type]
+ return tuple({
+ **trait,
+ "db": {
+ **trait["db"],
+ **dataset_names_info.get(trait["db"]["dataset_name"], {}),
+ **dataset_groups.get(trait["db"]["dataset_name"], {})
+ }
+ } for trait in traits)
+
+def probeset_datasets_names(conn: Any, threshold: int, dataset_names: Tuple[str, ...]):
+ """
+ Get the ID, DataScale and various name formats for a `ProbeSet` trait.
+ """
+ query = (
+ "SELECT Id AS dataset_id, Name AS dataset_name, "
+ "FullName AS dataset_fullname, ShortName AS dataset_shortname, "
+ "DataScale AS dataset_datascale "
+ "FROM ProbeSetFreeze "
+ "WHERE "
+ "public > %s "
+ "AND "
+ "(Name IN ({names}) OR FullName IN ({names}) OR ShortName IN ({names}))")
+ with conn.cursor(cursorclass=DictCursor) as cursor:
+ cursor.execute(
+ query.format(names=", ".join(["%s"] * len(dataset_names))),
+ (threshold,) +(dataset_names * 3))
+ return {ds["dataset_name"]: ds for ds in cursor.fetchall()}
+ return {}
+
+def probeset_datasets_groups(conn, dataset_names):
+ """
+ Retrieve the Group, and GroupID values for various ProbeSet trait types.
+ """
+ query = (
+ "SELECT ProbeSetFreeze.Name AS dataset_name, InbredSet.Name, "
+ "InbredSet.Id "
+ "FROM InbredSet, ProbeSetFreeze, ProbeFreeze "
+ "WHERE ProbeFreeze.InbredSetId = InbredSet.Id "
+ "AND ProbeFreeze.Id = ProbeSetFreeze.ProbeFreezeId "
+ "AND ProbeSetFreeze.Name IN ({names})").format(
+ names=", ".join(["%s"] * len(dataset_names)))
+ with conn.cursor(cursorclass=DictCursor) as cursor:
+ cursor.execute(query, tuple(dataset_names))
+ return organise_groups_by_dataset(cursor.fetchall())
+ return {}
+
+def probeset_traits_datasets(conn: Any, threshold, traits: Tuple[Dict]):
+ """Retrive datasets for 'ProbeSet' traits."""
+ dataset_names = tuple(set(trait["db"]["dataset_name"] for trait in traits))
+ dataset_names_info = probeset_datasets_names(conn, threshold, dataset_names)
+ dataset_groups = probeset_datasets_groups(conn, dataset_names)
+ return tuple({
+ **trait,
+ "db": {
+ **trait["db"],
+ **dataset_names_info.get(trait["db"]["dataset_name"], {}),
+ **dataset_groups.get(trait["db"]["dataset_name"], {})
+ }
+ } for trait in traits)
+
+def geno_datasets_names(conn, threshold, dataset_names):
+ """
+ Get the ID, DataScale and various name formats for a `Geno` trait.
+ """
+ query = (
+ "SELECT Id AS dataset_id, Name AS dataset_name, "
+ "FullName AS dataset_fullname, ShortName AS dataset_short_name "
+ "FROM GenoFreeze "
+ "WHERE "
+ "public > %s "
+ "AND "
+ "(Name = ({names}) OR FullName = ({names}) OR ShortName = ({names}))")
+ with conn.cursor(cursorclass=DictCursor) as cursor:
+ cursor.execute(
+ query.format(names=", ".join(["%s"] * len(dataset_names))),
+ (threshold,) + tuple(dataset_names))
+ return ...
+ return {}
+
+def geno_datasets_groups(conn, dataset_names):
+ """
+ Retrieve the Group, and GroupID values for various Geno trait types.
+ """
+ query = (
+ "SELECT GenoFreeze.Name AS dataset_name, InbredSet.Name, InbredSet.Id "
+ "FROM InbredSet, GenoFreeze "
+ "WHERE GenoFreeze.InbredSetId = InbredSet.Id "
+ "AND GenoFreeze.Name IN ({names})").format(
+ names=", ".join(["%s"] * len(dataset_names)))
+ with conn.cursor(cursorclass=DictCursor) as cursor:
+ cursor.execute(query, tuple(dataset_names))
+ return organise_groups_by_dataset(cursor.fetchall())
+ return {}
+
+def geno_traits_datasets(conn: Any, threshold: int, traits: Tuple[Dict]):
+ """Retrieve datasets for 'Geno' traits."""
+ dataset_names = tuple(set(trait["db"]["dataset_name"] for trait in traits))
+ dataset_names_info = geno_datasets_names(conn, threshold, dataset_names)
+ dataset_groups = geno_datasets_groups(conn, dataset_names)
+ return tuple({
+ **trait,
+ "db": {
+ **trait["db"],
+ **dataset_names_info.get(trait["db"]["dataset_name"], {}),
+ **dataset_groups.get(trait["db"]["dataset_name"], {})
+ }
+ } for trait in traits)
+
+def temp_datasets_names(conn, threshold, dataset_names):
+ """
+ Get the ID, DataScale and various name formats for a `Temp` trait.
+ """
+ query = (
+ "SELECT Id, Name, FullName, ShortName "
+ "FROM TempFreeze "
+ "WHERE "
+ "public > %s "
+ "AND "
+ "(Name = ({names}) OR FullName = ({names}) OR ShortName = ({names}))")
+ with conn.cursor(cursorclass=DictCursor) as cursor:
+ cursor.execute(
+ query.format(names=", ".join(["%s"] * len(dataset_names))),
+ (threshold,) +(dataset_names * 3))
+ return {ds["dataset_name"]: ds for ds in cursor.fetchall()}
+ return {}
+
+def temp_datasets_groups(conn, dataset_names):
+ """
+ Retrieve the Group, and GroupID values for `Temp` trait types.
+ """
+ query = (
+ "SELECT Temp.Name AS dataset_name, InbredSet.Name, InbredSet.Id "
+ "FROM InbredSet, Temp "
+ "WHERE Temp.InbredSetId = InbredSet.Id "
+ "AND Temp.Name IN ({names})").format(
+ names=", ".join(["%s"] * len(dataset_names)))
+ with conn.cursor(cursorclass=DictCursor) as cursor:
+ cursor.execute(query, tuple(dataset_names))
+ return organise_groups_by_dataset(cursor.fetchall())
+ return {}
+
+def temp_traits_datasets(conn: Any, threshold: int, traits: Tuple[Dict]):
+ """
+ Retrieve datasets for 'Temp' traits.
+ """
+ dataset_names = tuple(set(trait["db"]["dataset_name"] for trait in traits))
+ dataset_names_info = temp_datasets_names(conn, threshold, dataset_names)
+ dataset_groups = temp_datasets_groups(conn, dataset_names)
+ return tuple({
+ **trait,
+ "db": {
+ **trait["db"],
+ **dataset_names_info.get(trait["db"]["dataset_name"], {}),
+ **dataset_groups.get(trait["db"]["dataset_name"], {})
+ }
+ } for trait in traits)
+
+def set_confidential(traits):
+ """
+ Set the confidential field for traits of type `Publish`.
+ """
+ return tuple({
+ **trait,
+ "confidential": (
+ True if (# pylint: disable=[R1719]
+ trait.get("pre_publication_description")
+ and not trait.get("pubmed_id"))
+ else False)
+ } for trait in traits)
+
+def query_qtl_info(conn, query, traits, dataset_ids):
+ """
+ Utility: Run the `query` to get the QTL information for the given `traits`.
+ """
+ with conn.cursor(cursorclass=DictCursor) as cursor:
+ cursor.execute(
+ query,
+ tuple(trait["trait_name"] for trait in traits) + dataset_ids)
+ results = {
+ row["trait_name"]: {
+ key: val for key, val in row if key != "trait_name"
+ } for row in cursor.fetchall()
+ }
+ return tuple(
+ {**trait, **results.get(trait["trait_name"], {})}
+ for trait in traits)
+
+def set_publish_qtl_info(conn, qtl, traits):
+ """
+ Load extra QTL information for `Publish` traits
+ """
+ if qtl:
+ dataset_ids = set(trait["db"]["dataset_id"] for trait in traits)
+ query = (
+ "SELECT PublishXRef.Id AS trait_name, PublishXRef.Locus, "
+ "PublishXRef.LRS, PublishXRef.additive "
+ "FROM PublishXRef, PublishFreeze "
+ "WHERE PublishXRef.Id IN ({trait_names}) "
+ "AND PublishXRef.InbredSetId = PublishFreeze.InbredSetId "
+ "AND PublishFreeze.Id IN ({dataset_ids})").format(
+ trait_names=", ".join(["%s"] * len(traits)),
+ dataset_ids=", ".join(["%s"] * len(dataset_ids)))
+ return query_qtl_info(conn, query, traits, tuple(dataset_ids))
+ return traits
+
+def set_probeset_qtl_info(conn, qtl, traits):
+ """
+ Load extra QTL information for `ProbeSet` traits
+ """
+ if qtl:
+ dataset_ids = tuple(set(trait["db"]["dataset_id"] for trait in traits))
+ query = (
+ "SELECT ProbeSet.Name AS trait_name, ProbeSetXRef.Locus, "
+ "ProbeSetXRef.LRS, ProbeSetXRef.pValue, "
+ "ProbeSetXRef.mean, ProbeSetXRef.additive "
+ "FROM ProbeSetXRef, ProbeSet "
+ "WHERE ProbeSetXRef.ProbeSetId = ProbeSet.Id "
+ " AND ProbeSet.Name IN ({trait_names}) "
+ "AND ProbeSetXRef.ProbeSetFreezeId IN ({dataset_ids})").format(
+ trait_names=", ".join(["%s"] * len(traits)),
+ dataset_ids=", ".join(["%s"] * len(dataset_ids)))
+ return query_qtl_info(conn, query, traits, tuple(dataset_ids))
+ return traits
+
+def set_sequence(conn, traits):
+ """
+ Retrieve 'ProbeSet' traits sequence information
+ """
+ dataset_names = set(trait["db"]["dataset_name"] for trait in traits)
+ query = (
+ "SELECT ProbeSet.Name as trait_name, ProbeSet.BlatSeq "
+ "FROM ProbeSet, ProbeSetFreeze, ProbeSetXRef "
+ "WHERE ProbeSet.Id=ProbeSetXRef.ProbeSetId "
+ "AND ProbeSetFreeze.Id = ProbeSetXRef.ProbeSetFreezeId "
+ "AND ProbeSet.Name IN ({trait_names}) "
+ "AND ProbeSetFreeze.Name IN ({dataset_names})").format(
+ trait_names=", ".join(["%s"] * len(traits)),
+ dataset_names=", ".join(["%s"] * len(dataset_names)))
+ with conn.cursor(cursorclass=DictCursor) as cursor:
+ cursor.execute(
+ query,
+ (tuple(trait["trait_name"] for trait in traits) +
+ tuple(dataset_names)))
+ results = {
+ row["trait_name"]: {
+ key: val for key, val in row.items() if key != "trait_name"
+ } for row in cursor.fetchall()
+ }
+ return tuple(
+ {
+ **trait,
+ **results.get(trait["trait_name"], {})
+ } for trait in traits)
+ return traits
+
+def set_homologene_id(conn, traits):
+ """
+ Retrieve and set the 'homologene_id' values for ProbeSet traits.
+ """
+ geneids = set(trait["geneid"] for trait in traits)
+ groups = set(trait["db"]["group"] for trait in traits)
+ query = (
+ "SELECT InbredSet.Name AS `group`, Homologene.GeneId AS geneid, "
+ "HomologeneId "
+ "FROM Homologene, Species, InbredSet "
+ "WHERE Homologene.GeneId = ({geneids}) "
+ "AND InbredSet.Name = ({groups}) "
+ "AND InbredSet.SpeciesId = Species.Id "
+ "AND Species.TaxonomyId = Homologene.TaxonomyId").format(
+ geneids=", ".join(["%s"] * len(geneids)),
+ groups=", ".join(["%s"] * len(groups)))
+ with conn.cursor(cursorclass=DictCursor) as cursor:
+ cursor.execute(query, (tuple(geneids) + tuple(groups)))
+ results = {
+ row["group"]: {
+ row["geneid"]: {
+ key: val for key, val in row.items()
+ if key not in ("group", "geneid")
+ }
+ } for row in cursor.fetchall()
+ }
+ return tuple(
+ {
+ **trait, **results.get(
+ trait["db"]["group"], {}).get(trait["geneid"], {})
+ } for trait in traits)
+ return traits
+
+def traits_datasets(conn, threshold, traits):
+ """
+ Retrieve datasets for various `traits`.
+ """
+ dataset_fns = {
+ "Temp": temp_traits_datasets,
+ "Geno": geno_traits_datasets,
+ "Publish": publish_traits_datasets,
+ "ProbeSet": probeset_traits_datasets
+ }
+ def __organise_by_type__(acc, trait):
+ dataset_type = trait["db"]["dataset_type"]
+ return {
+ **acc,
+ dataset_type: acc.get(dataset_type, tuple()) + (trait,)
+ }
+ with_datasets = {
+ trait["trait_fullname"]: trait for trait in (
+ item for sublist in (
+ dataset_fns[dtype](conn, threshold, ttraits)
+ for dtype, ttraits
+ in reduce(__organise_by_type__, traits, {}).items())
+ for item in sublist)}
+ return tuple(
+ {**trait, **with_datasets.get(trait["trait_fullname"], {})}
+ for trait in traits)
+
+def traits_info(
+ conn: Any, threshold: int, traits_fullnames: Tuple[str, ...],
+ qtl=None) -> Tuple[Dict[str, Any], ...]:
+ """
+ Retrieve basic trait information for multiple `traits`.
+
+ This is a rework of the `gn3.db.traits.retrieve_trait_info` function.
+ """
+ def __organise_by_dataset_type__(acc, trait):
+ dataset_type = trait["db"]["dataset_type"]
+ return {
+ **acc,
+ dataset_type: acc.get(dataset_type, tuple()) + (trait,)
+ }
+ traits = traits_datasets(
+ conn, threshold,
+ tuple(build_trait_name(trait) for trait in traits_fullnames))
+ traits_fns = {
+ "Publish": compose(
+ set_confidential, partial(set_publish_qtl_info, conn, qtl),
+ partial(publish_traits_info, conn),
+ partial(publish_traits_datasets, conn, threshold)),
+ "ProbeSet": compose(
+ partial(set_sequence, conn),
+ partial(set_probeset_qtl_info, conn, qtl),
+ partial(set_homologene_id, conn),
+ partial(probeset_traits_info, conn),
+ partial(probeset_traits_datasets, conn, threshold)),
+ "Geno": compose(
+ partial(geno_traits_info, conn),
+ partial(geno_traits_datasets, conn, threshold)),
+ "Temp": compose(
+ partial(temp_traits_info, conn),
+ partial(temp_traits_datasets, conn, threshold))
+ }
+ return tuple(
+ trait for sublist in (# type: ignore[var-annotated]
+ traits_fns[dataset_type](traits)
+ for dataset_type, traits
+ in reduce(__organise_by_dataset_type__, traits, {}).items())
+ for trait in sublist)