diff options
| -rw-r--r-- | gn3/db/correlations.py | 139 | ||||
| -rw-r--r-- | gn3/db/species.py | 31 | ||||
| -rw-r--r-- | gn3/partial_correlations.py | 38 | ||||
| -rw-r--r-- | tests/unit/test_partial_correlations.py | 64 |
4 files changed, 269 insertions, 3 deletions
diff --git a/gn3/db/correlations.py b/gn3/db/correlations.py new file mode 100644 index 0000000..67cfef9 --- /dev/null +++ b/gn3/db/correlations.py @@ -0,0 +1,139 @@ +""" +This module will hold functions that are used in the (partial) correlations +feature to access the database to retrieve data needed for computations. +""" + +from typing import Any + +from gn3.random import random_string +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) # {trait_name: lit_corr for trait_name, lit_corr 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_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) |