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-rw-r--r--gn3/data_helpers.py25
-rw-r--r--gn3/db/correlations.py318
-rw-r--r--gn3/db/species.py31
-rw-r--r--gn3/partial_correlations.py38
-rw-r--r--tests/unit/test_data_helpers.py37
-rw-r--r--tests/unit/test_partial_correlations.py64
6 files changed, 510 insertions, 3 deletions
diff --git a/gn3/data_helpers.py b/gn3/data_helpers.py
new file mode 100644
index 0000000..f0d971e
--- /dev/null
+++ b/gn3/data_helpers.py
@@ -0,0 +1,25 @@
+"""
+This module will hold generic functions that can operate on a wide-array of
+data structures.
+"""
+
+from math import ceil
+from functools import reduce
+from typing import Any, Tuple, Sequence
+
+def partition_all(num: int, items: Sequence[Any]) -> Tuple[Tuple[Any, ...], ...]:
+ """
+ Given a sequence `items`, return a new sequence of the same type as `items`
+ with the data partitioned into sections of `n` items per partition.
+
+ This is an approximation of clojure's `partition-all` function.
+ """
+ def __compute_start_stop__(acc, iteration):
+ start = iteration * num
+ return acc + ((start, start + num),)
+
+ iterations = range(ceil(len(items) / num))
+ return tuple([# type: ignore[misc]
+ tuple(items[start:stop]) for start, stop # type: ignore[has-type]
+ in reduce(
+ __compute_start_stop__, iterations, tuple())])
diff --git a/gn3/db/correlations.py b/gn3/db/correlations.py
new file mode 100644
index 0000000..87ab082
--- /dev/null
+++ b/gn3/db/correlations.py
@@ -0,0 +1,318 @@
+"""
+This module will hold functions that are used in the (partial) correlations
+feature to access the database to retrieve data needed for computations.
+"""
+
+from functools import reduce
+from typing import Any, Dict, Tuple
+
+from gn3.random import random_string
+from gn3.data_helpers import partition_all
+from gn3.db.species import translate_to_mouse_gene_id
+
+def get_filename(target_db_name: str, conn: Any) -> str:
+ """
+ Retrieve the name of the reference database file with which correlations are
+ computed.
+
+ This is a migration of the
+ `web.webqtl.correlation.CorrelationPage.getFileName` function in
+ GeneNetwork1.
+ """
+ with conn.cursor() as cursor:
+ cursor.execute(
+ "SELECT Id, FullName from ProbeSetFreeze WHERE Name-%s",
+ target_db_name)
+ result = cursor.fetchone()
+ if result:
+ return "ProbeSetFreezeId_{tid}_FullName_{fname}.txt".format(
+ tid=result[0],
+ fname=result[1].replace(' ', '_').replace('/', '_'))
+
+ return ""
+
+def build_temporary_literature_table(
+ species: str, gene_id: int, return_number: int, conn: Any) -> str:
+ """
+ Build and populate a temporary table to hold the literature correlation data
+ to be used in computations.
+
+ "This is a migration of the
+ `web.webqtl.correlation.CorrelationPage.getTempLiteratureTable` function in
+ GeneNetwork1.
+ """
+ def __translated_species_id(row, cursor):
+ if species == "mouse":
+ return row[1]
+ query = {
+ "rat": "SELECT rat FROM GeneIDXRef WHERE mouse=%s",
+ "human": "SELECT human FROM GeneIDXRef WHERE mouse=%d"}
+ if species in query.keys():
+ cursor.execute(query[species], row[1])
+ record = cursor.fetchone()
+ if record:
+ return record[0]
+ return None
+ return None
+
+ temp_table_name = f"TOPLITERATURE{random_string(8)}"
+ with conn.cursor as cursor:
+ mouse_geneid = translate_to_mouse_gene_id(species, gene_id, conn)
+ data_query = (
+ "SELECT GeneId1, GeneId2, value FROM LCorrRamin3 "
+ "WHERE GeneId1 = %(mouse_gene_id)s "
+ "UNION ALL "
+ "SELECT GeneId2, GeneId1, value FROM LCorrRamin3 "
+ "WHERE GeneId2 = %(mouse_gene_id)s "
+ "AND GeneId1 != %(mouse_gene_id)s")
+ cursor.execute(
+ (f"CREATE TEMPORARY TABLE {temp_table_name} ("
+ "GeneId1 int(12) unsigned, "
+ "GeneId2 int(12) unsigned PRIMARY KEY, "
+ "value double)"))
+ cursor.execute(data_query, mouse_gene_id=mouse_geneid)
+ literature_data = [
+ {"GeneId1": row[0], "GeneId2": row[1], "value": row[2]}
+ for row in cursor.fetchall()
+ if __translated_species_id(row, cursor)]
+
+ cursor.execute(
+ (f"INSERT INTO {temp_table_name} "
+ "VALUES (%(GeneId1)s, %(GeneId2)s, %(value)s)"),
+ literature_data[0:(2 * return_number)])
+
+ return temp_table_name
+
+def fetch_geno_literature_correlations(temp_table: str) -> str:
+ """
+ Helper function for `fetch_literature_correlations` below, to build query
+ for `Geno*` tables.
+ """
+ return (
+ f"SELECT Geno.Name, {temp_table}.value "
+ "FROM Geno, GenoXRef, GenoFreeze "
+ f"LEFT JOIN {temp_table} ON {temp_table}.GeneId2=ProbeSet.GeneId "
+ "WHERE ProbeSet.GeneId IS NOT NULL "
+ f"AND {temp_table}.value IS NOT NULL "
+ "AND GenoXRef.GenoFreezeId = GenoFreeze.Id "
+ "AND GenoFreeze.Name = %(db_name)s "
+ "AND Geno.Id=GenoXRef.GenoId "
+ "ORDER BY Geno.Id")
+
+def fetch_probeset_literature_correlations(temp_table: str) -> str:
+ """
+ Helper function for `fetch_literature_correlations` below, to build query
+ for `ProbeSet*` tables.
+ """
+ return (
+ f"SELECT ProbeSet.Name, {temp_table}.value "
+ "FROM ProbeSet, ProbeSetXRef, ProbeSetFreeze "
+ "LEFT JOIN {temp_table} ON {temp_table}.GeneId2=ProbeSet.GeneId "
+ "WHERE ProbeSet.GeneId IS NOT NULL "
+ "AND {temp_table}.value IS NOT NULL "
+ "AND ProbeSetXRef.ProbeSetFreezeId = ProbeSetFreeze.Id "
+ "AND ProbeSetFreeze.Name = %(db_name)s "
+ "AND ProbeSet.Id=ProbeSetXRef.ProbeSetId "
+ "ORDER BY ProbeSet.Id")
+
+def fetch_literature_correlations(
+ species: str, gene_id: int, dataset: dict, return_number: int,
+ conn: Any) -> dict:
+ """
+ Gather the literature correlation data and pair it with trait id string(s).
+
+ This is a migration of the
+ `web.webqtl.correlation.CorrelationPage.fetchLitCorrelations` function in
+ GeneNetwork1.
+ """
+ temp_table = build_temporary_literature_table(
+ species, gene_id, return_number, conn)
+ query_fns = {
+ "Geno": fetch_geno_literature_correlations,
+ # "Temp": fetch_temp_literature_correlations,
+ # "Publish": fetch_publish_literature_correlations,
+ "ProbeSet": fetch_probeset_literature_correlations}
+ with conn.cursor as cursor:
+ cursor.execute(
+ query_fns[dataset["dataset_type"]](temp_table),
+ db_name=dataset["dataset_name"])
+ results = cursor.fetchall()
+ cursor.execute("DROP TEMPORARY TABLE %s", temp_table)
+ return dict(results)
+
+def compare_tissue_correlation_absolute_values(val1, val2):
+ """
+ Comparison function for use when sorting tissue correlation values.
+
+ This is a partial migration of the
+ `web.webqtl.correlation.CorrelationPage.getTempTissueCorrTable` function in
+ GeneNetwork1."""
+ try:
+ if abs(val1) < abs(val2):
+ return 1
+ if abs(val1) == abs(val2):
+ return 0
+ return -1
+ except TypeError:
+ return 0
+
+def fetch_symbol_value_pair_dict(
+ symbol_list: Tuple[str, ...], data_id_dict: dict,
+ conn: Any) -> Dict[str, Tuple[float, ...]]:
+ """
+ Map each gene symbols to the corresponding tissue expression data.
+
+ This is a migration of the
+ `web.webqtl.correlation.correlationFunction.getSymbolValuePairDict` function
+ in GeneNetwork1.
+ """
+ data_ids = {
+ symbol: data_id_dict.get(symbol) for symbol in symbol_list
+ if data_id_dict.get(symbol) is not None
+ }
+ query = "SELECT Id, value FROM TissueProbeSetData WHERE Id IN %(data_ids)s"
+ with conn.cursor() as cursor:
+ cursor.execute(
+ query,
+ data_ids=tuple(data_ids.values()))
+ value_results = cursor.fetchall()
+ return {
+ key: tuple(row[1] for row in value_results if row[0] == key)
+ for key in data_ids.keys()
+ }
+
+ return {}
+
+def fetch_gene_symbol_tissue_value_dict(
+ symbol_list: Tuple[str, ...], data_id_dict: dict, conn: Any,
+ limit_num: int = 1000) -> dict:#getGeneSymbolTissueValueDict
+ """
+ Wrapper function for `gn3.db.correlations.fetch_symbol_value_pair_dict`.
+
+ This is a migrations of the
+ `web.webqtl.correlation.correlationFunction.getGeneSymbolTissueValueDict` in
+ GeneNetwork1.
+ """
+ count = len(symbol_list)
+ if count != 0 and count <= limit_num:
+ return fetch_symbol_value_pair_dict(symbol_list, data_id_dict, conn)
+
+ if count > limit_num:
+ return {
+ key: value for dct in [
+ fetch_symbol_value_pair_dict(sl, data_id_dict, conn)
+ for sl in partition_all(limit_num, symbol_list)]
+ for key, value in dct.items()
+ }
+
+ return {}
+
+def fetch_tissue_probeset_xref_info(
+ gene_name_list: Tuple[str, ...], probeset_freeze_id: int,
+ conn: Any) -> Tuple[tuple, dict, dict, dict, dict, dict, dict]:
+ """
+ Retrieve the ProbeSet XRef information for tissues.
+
+ This is a migration of the
+ `web.webqtl.correlation.correlationFunction.getTissueProbeSetXRefInfo`
+ function in GeneNetwork1."""
+ with conn.cursor() as cursor:
+ if len(gene_name_list) == 0:
+ query = (
+ "SELECT t.Symbol, t.GeneId, t.DataId, t.Chr, t.Mb, "
+ "t.description, t.Probe_Target_Description "
+ "FROM "
+ "("
+ " SELECT Symbol, max(Mean) AS maxmean "
+ " FROM TissueProbeSetXRef "
+ " WHERE TissueProbeSetFreezeId=%(probeset_freeze_id)s "
+ " AND Symbol != '' "
+ " AND Symbol IS NOT NULL "
+ " GROUP BY Symbol"
+ ") AS x "
+ "INNER JOIN TissueProbeSetXRef AS t ON t.Symbol = x.Symbol "
+ "AND t.Mean = x.maxmean")
+ cursor.execute(query, probeset_freeze_id=probeset_freeze_id)
+ else:
+ query = (
+ "SELECT t.Symbol, t.GeneId, t.DataId, t.Chr, t.Mb, "
+ "t.description, t.Probe_Target_Description "
+ "FROM "
+ "("
+ " SELECT Symbol, max(Mean) AS maxmean "
+ " FROM TissueProbeSetXRef "
+ " WHERE TissueProbeSetFreezeId=%(probeset_freeze_id)s "
+ " AND Symbol in %(symbols)s "
+ " GROUP BY Symbol"
+ ") AS x "
+ "INNER JOIN TissueProbeSetXRef AS t ON t.Symbol = x.Symbol "
+ "AND t.Mean = x.maxmean")
+ cursor.execute(
+ query, probeset_freeze_id=probeset_freeze_id,
+ symbols=tuple(gene_name_list))
+
+ results = cursor.fetchall()
+
+ return reduce(
+ lambda acc, item: (
+ acc[0] + (item[0],),
+ {**acc[1], item[0].lower(): item[1]},
+ {**acc[1], item[0].lower(): item[2]},
+ {**acc[1], item[0].lower(): item[3]},
+ {**acc[1], item[0].lower(): item[4]},
+ {**acc[1], item[0].lower(): item[5]},
+ {**acc[1], item[0].lower(): item[6]}),
+ results or tuple(),
+ (tuple(), {}, {}, {}, {}, {}, {}))
+
+def correlations_of_all_tissue_traits() -> Tuple[dict, dict]:
+ """
+ This is a migration of the
+ `web.webqtl.correlation.CorrelationPage.calculateCorrOfAllTissueTrait`
+ function in GeneNetwork1.
+ """
+ raise Exception("Unimplemented!!!")
+ return ({}, {})
+
+def build_temporary_tissue_correlations_table(
+ trait_symbol: str, probeset_freeze_id: int, method: str,
+ return_number: int, conn: Any) -> str:
+ """
+ Build a temporary table to hold the tissue correlations data.
+
+ This is a migration of the
+ `web.webqtl.correlation.CorrelationPage.getTempTissueCorrTable` function in
+ GeneNetwork1."""
+ raise Exception("Unimplemented!!!")
+ return ""
+
+def fetch_tissue_correlations(
+ dataset: dict, trait_symbol: str, probeset_freeze_id: int, method: str,
+ return_number: int, conn: Any) -> dict:
+ """
+ Pair tissue correlations data with a trait id string.
+
+ This is a migration of the
+ `web.webqtl.correlation.CorrelationPage.fetchTissueCorrelations` function in
+ GeneNetwork1.
+ """
+ temp_table = build_temporary_tissue_correlations_table(
+ trait_symbol, probeset_freeze_id, method, return_number, conn)
+ with conn.cursor() as cursor:
+ cursor.execute(
+ (
+ f"SELECT ProbeSet.Name, {temp_table}.Correlation, "
+ f"{temp_table}.PValue "
+ "FROM (ProbeSet, ProbeSetXRef, ProbeSetFreeze) "
+ "LEFT JOIN {temp_table} ON {temp_table}.Symbol=ProbeSet.Symbol "
+ "WHERE ProbeSetFreeze.Name = %(db_name) "
+ "AND ProbeSetFreeze.Id=ProbeSetXRef.ProbeSetFreezeId "
+ "AND ProbeSet.Id = ProbeSetXRef.ProbeSetId "
+ "AND ProbeSet.Symbol IS NOT NULL "
+ "AND %s.Correlation IS NOT NULL"),
+ db_name=dataset["dataset_name"])
+ results = cursor.fetchall()
+ cursor.execute("DROP TEMPORARY TABLE %s", temp_table)
+ return {
+ trait_name: (tiss_corr, tiss_p_val)
+ for trait_name, tiss_corr, tiss_p_val in results}
diff --git a/gn3/db/species.py b/gn3/db/species.py
index 0deae4e..1e5015f 100644
--- a/gn3/db/species.py
+++ b/gn3/db/species.py
@@ -30,3 +30,34 @@ def get_chromosome(name: str, is_species: bool, conn: Any) -> Optional[Tuple]:
with conn.cursor() as cursor:
cursor.execute(_sql)
return cursor.fetchall()
+
+def translate_to_mouse_gene_id(species: str, geneid: int, conn: Any) -> int:
+ """
+ Translate rat or human geneid to mouse geneid
+
+ This is a migration of the
+ `web.webqtl.correlation/CorrelationPage.translateToMouseGeneID` function in
+ GN1
+ """
+ assert species in ("rat", "mouse", "human"), "Invalid species"
+ if geneid is None:
+ return 0
+
+ if species == "mouse":
+ return geneid
+
+ with conn.cursor as cursor:
+ if species == "rat":
+ cursor.execute(
+ "SELECT mouse FROM GeneIDXRef WHERE rat = %s", geneid)
+ rat_geneid = cursor.fetchone()
+ if rat_geneid:
+ return rat_geneid[0]
+
+ cursor.execute(
+ "SELECT mouse FROM GeneIDXRef WHERE human = %s", geneid)
+ human_geneid = cursor.fetchone()
+ if human_geneid:
+ return human_geneid[0]
+
+ return 0 # default if all else fails
diff --git a/gn3/partial_correlations.py b/gn3/partial_correlations.py
index c556d10..1fb0ccc 100644
--- a/gn3/partial_correlations.py
+++ b/gn3/partial_correlations.py
@@ -6,7 +6,7 @@ GeneNetwork1.
"""
from functools import reduce
-from typing import Any, Sequence
+from typing import Any, Tuple, Sequence
def control_samples(controls: Sequence[dict], sampleslist: Sequence[str]):
"""
@@ -86,3 +86,39 @@ def fix_samples(primary_trait: dict, control_traits: Sequence[dict]) -> Sequence
control_vals_vars[0],
tuple(primary_trait[sample]["variance"] for sample in primary_samples),
control_vals_vars[1])
+
+def find_identical_traits(
+ primary_name: str, primary_value: float, control_names: Tuple[str, ...],
+ control_values: Tuple[float, ...]) -> Tuple[str, ...]:
+ """
+ Find traits that have the same value when the values are considered to
+ 3 decimal places.
+
+ This is a migration of the
+ `web.webqtl.correlation.correlationFunction.findIdenticalTraits` function in
+ GN1.
+ """
+ def __merge_identicals__(
+ acc: Tuple[str, ...],
+ ident: Tuple[str, Tuple[str, ...]]) -> Tuple[str, ...]:
+ return acc + ident[1]
+
+ def __dictify_controls__(acc, control_item):
+ ckey = "{:.3f}".format(control_item[0])
+ return {**acc, ckey: acc.get(ckey, tuple()) + (control_item[1],)}
+
+ return (reduce(## for identical control traits
+ __merge_identicals__,
+ (item for item in reduce(# type: ignore[var-annotated]
+ __dictify_controls__, zip(control_values, control_names),
+ {}).items() if len(item[1]) > 1),
+ tuple())
+ or
+ reduce(## If no identical control traits, try primary and controls
+ __merge_identicals__,
+ (item for item in reduce(# type: ignore[var-annotated]
+ __dictify_controls__,
+ zip((primary_value,) + control_values,
+ (primary_name,) + control_names), {}).items()
+ if len(item[1]) > 1),
+ tuple()))
diff --git a/tests/unit/test_data_helpers.py b/tests/unit/test_data_helpers.py
new file mode 100644
index 0000000..1eec3cc
--- /dev/null
+++ b/tests/unit/test_data_helpers.py
@@ -0,0 +1,37 @@
+"""
+Test functions in gn3.data_helpers
+"""
+
+from unittest import TestCase
+
+from gn3.data_helpers import partition_all
+
+class TestDataHelpers(TestCase):
+ """
+ Test functions in gn3.data_helpers
+ """
+
+ def test_partition_all(self):
+ """
+ Test that `gn3.data_helpers.partition_all` partitions sequences as expected.
+
+ Given:
+ - `num`: The number of items per partition
+ - `items`: A sequence of items
+ When:
+ - The arguments above are passed to the `gn3.data_helpers.partition_all`
+ Then:
+ - Return a new sequence with partitions, each of which has `num`
+ items in the same order as those in `items`, save for the last
+ partition which might have fewer items than `num`.
+ """
+ for count, items, expected in (
+ (1, [0, 1, 2, 3], ((0,), (1,), (2,), (3,))),
+ (3, (0, 1, 2, 3, 4, 5, 6, 7, 8, 9),
+ ((0, 1, 2), (3, 4, 5), (6, 7, 8), (9, ))),
+ (4, [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
+ ((0, 1, 2, 3), (4, 5, 6, 7), (8, 9))),
+ (13, [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
+ ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9), ))):
+ with self.subTest(n=count, items=items):
+ self.assertEqual(partition_all(count, items), expected)
diff --git a/tests/unit/test_partial_correlations.py b/tests/unit/test_partial_correlations.py
index 7631a71..60e54c1 100644
--- a/tests/unit/test_partial_correlations.py
+++ b/tests/unit/test_partial_correlations.py
@@ -4,7 +4,8 @@ from unittest import TestCase
from gn3.partial_correlations import (
fix_samples,
control_samples,
- dictify_by_samples)
+ dictify_by_samples,
+ find_identical_traits)
sampleslist = ["B6cC3-1", "BXD1", "BXD12", "BXD16", "BXD19", "BXD2"]
control_traits = (
@@ -106,6 +107,8 @@ class TestPartialCorrelations(TestCase):
def test_dictify_by_samples(self):
"""
+ Test that `dictify_by_samples` generates the appropriate dict
+
Given:
a sequence of sequences with sample names, values and variances, as
in the output of `gn3.partial_correlations.control_samples` or
@@ -133,7 +136,34 @@ class TestPartialCorrelations(TestCase):
dictified_control_samples)
def test_fix_samples(self):
- """Test that fix_samples fixes the values"""
+ """
+ Test that `fix_samples` returns only the common samples
+
+ Given:
+ - A primary trait
+ - A sequence of control samples
+ When:
+ - The two arguments are passed to `fix_samples`
+ Then:
+ - Only the names of the samples present in the primary trait that
+ are also present in ALL the control traits are present in the
+ return value
+ - Only the values of the samples present in the primary trait that
+ are also present in ALL the control traits are present in the
+ return value
+ - ALL the values for ALL the control traits are present in the
+ return value
+ - Only the variances of the samples present in the primary trait
+ that are also present in ALL the control traits are present in the
+ return value
+ - ALL the variances for ALL the control traits are present in the
+ return value
+ - The return value is a tuple of the above items, in the following
+ order:
+ ((sample_names, ...), (primary_trait_values, ...),
+ (control_traits_values, ...), (primary_trait_variances, ...)
+ (control_traits_variances, ...))
+ """
self.assertEqual(
fix_samples(
{"B6cC3-1": {"sample_name": "B6cC3-1", "value": 7.51879,
@@ -149,3 +179,33 @@ class TestPartialCorrelations(TestCase):
(None,),
(None, None, None, None, None, None, None, None, None, None, None,
None, None)))
+
+ def test_find_identical_traits(self):
+ """
+ Test `gn3.partial_correlations.find_identical_traits`.
+
+ Given:
+ - the name of a primary trait
+ - the value of a primary trait
+ - a sequence of names of control traits
+ - a sequence of values of control traits
+ When:
+ - the arguments above are passed to the `find_identical_traits`
+ function
+ Then:
+ - Return ALL trait names that have the same value when up to three
+ decimal places are considered
+ """
+ for primn, primv, contn, contv, expected in (
+ ("pt", 12.98395, ("ct0", "ct1", "ct2"),
+ (0.1234, 2.3456, 3.4567), tuple()),
+ ("pt", 12.98395, ("ct0", "ct1", "ct2"),
+ (12.98354, 2.3456, 3.4567), ("pt", "ct0")),
+ ("pt", 12.98395, ("ct0", "ct1", "ct2", "ct3"),
+ (0.1234, 2.3456, 0.1233, 4.5678), ("ct0", "ct2"))
+ ):
+ with self.subTest(
+ primary_name=primn, primary_value=primv,
+ control_names=contn, control_values=contv):
+ self.assertEqual(
+ find_identical_traits(primn, primv, contn, contv), expected)