Added parser for the KinAce database of kinase-substrate phosphorylat…

Common/data_sources.py

@@ -18,6 +18,7 @@
 HMDB = 'HMDB'
 HUMAN_GOA = 'HumanGOA'
 INTACT = 'IntAct'
+KINACE = 'KinAce'
 MONARCH_KG = 'MonarchKG'
 MONDO_PROPS = 'MONDOProps'
 ONTOLOGICAL_HIERARCHY = 'OntologicalHierarchy'
@@ -60,6 +61,7 @@
     HUMAN_GOA: ("parsers.GOA.src.loadGOA", "HumanGOALoader"),
     HUMAN_STRING: ("parsers.STRING.src.loadSTRINGDB", "HumanSTRINGDBLoader"),
     INTACT: ("parsers.IntAct.src.loadIA", "IALoader"),
+    KINACE: ("parsers.KinAce.src.loadKinAce", "KinAceLoader"),
     MONARCH_KG: ("parsers.monarchkg.src.loadMonarchKG", "MonarchKGLoader"),
     MONDO_PROPS: ("parsers.MONDOProperties.src.loadMP", "MPLoader"),
     ONTOLOGICAL_HIERARCHY: ("parsers.UberGraph.src.loadUG", "OHLoader"),

parsers/KinAce/src/loadKinAce.py

@@ -0,0 +1,112 @@
+import os
+import enum
+from zipfile import ZipFile as zipfile
+import pandas as pd
+
+from Common.utils import GetData
+from Common.loader_interface import SourceDataLoader
+from Common.extractor import Extractor
+from Common.node_types import PUBLICATIONS
+
+# Full Kinase-Substrate Phosphorylation Data.
+
+#make this reflect the column that the data is found in
+class BD_EDGEUMAN(enum.IntEnum):
+    KINASE = 1
+    SUBSTRATE = 2
+    P_SITE = 3
+    PRIMARY_SOURCE = 4
+    SECONDARY_SOURCE = 5
+
+##############
+# Class: Loading kinase-substrate phosphorylation reactions from KinAce
+# By: Jon-Michael Beasley
+# Date: 03/7/2024
+##############
+class KinAceLoader(SourceDataLoader):
+
+    source_id: str = 'KinAce'
+    provenance_id: str = 'infores:kinace'
+    description = "The KinAce web portal aggregates and visualizes the network of interactions between protein-kinases and their substrates in the human genome."
+    source_data_url = "https://kinace.kinametrix.com/session/ff792906de38db0d1c9900ac5882497b/download/download0?w="
+    license = "All data and download files in bindingDB are freely available under a 'Creative Commons BY 3.0' license.'"
+    attribution = 'https://kinace.kinametrix.com/#section-about'
+    parsing_version = '1.0'
+
+    def __init__(self, test_mode: bool = False, source_data_dir: str = None):
+        """
+        constructor
+        :param test_mode - sets the run into test mode
+        """
+        # call the super
+        super().__init__(test_mode=test_mode, source_data_dir=source_data_dir)
+
+        self.kinace_version = "2023-10-30"
+        #self.kinace_version = self.get_latest_source_version()
+        self.kinace_data_url = f"https://raw.githubusercontent.com/GauravPandeyLab/KinAce/master/data/{self.kinace_version}-kinace-dataset.zip"
+
+        self.archive_file_name = f"{self.kinace_version}-kinace-dataset.zip"
+        self.interactions_file_name = f"ksi_source.csv"
+        self.data_files = [self.interactions_file_name]
+
+    def get_latest_source_version(self) -> str:
+        """
+        gets the latest version of the data
+        :return:
+        """
+        if self.kinace_version:
+            return self.kinace_version
+
+        return f"{self.kinace_version}"
+
+    def get_data(self) -> int:
+        """
+        Gets the KinAce data.
+
+        """
+        data_puller = GetData()
+        source_url = f"{self.kinace_data_url}"
+        data_puller.pull_via_http(source_url, self.data_path)
+        with zipfile(os.path.join(self.data_path, self.archive_file_name), 'r') as zip_ref:
+            zip_ref.extract(self.interactions_file_name, self.data_path)
+        return True
+
+    def parse_data(self) -> dict:
+        """
+        Parses the data file for graph nodes/edges
+        We are going to group by kinase-substrate pair and aggregate all phosphorylation sites and primary/secondary sources.
+
+        :return: ret_val: load_metadata
+        """
+        print('ok parsing')
+        # with zipfile(os.path.join(self.data_path, self.archive_file_name), 'r') as zip_ref:
+        #     zip_ref.extract(self.interactions_file_name, self.data_path)
+        data = pd.read_csv(os.path.join(self.data_path, self.interactions_file_name))
+        data = data.groupby(["Kinase", "Substrate"]).agg({"Site": list, "PrimarySource": list, "SecondarySource": list}).reset_index()
+        # Define a function to deduplicate lists
+        def deduplicate_list(lst):
+            lst = [x for x in lst if x == x]
+            return list(set(lst))
+        # Apply deduplication function to each aggregated list
+        data['Site'] = data.apply(lambda row: list(set([x for x in row['Site'] if x==x])), axis=1)
+        data['PrimarySource'] = data.apply(lambda row: list(set([x for x in row['PrimarySource'] if x==x])), axis=1)
+        data['SecondarySource'] = data.apply(lambda row: list(set([x for x in row['SecondarySource'] if x==x])), axis=1)
+        data.to_csv(os.path.join(self.data_path, self.interactions_file_name))
+        extractor = Extractor(file_writer=self.output_file_writer)
+        with open(os.path.join(self.data_path, self.interactions_file_name), 'rt') as fp:
+            extractor.csv_extract(fp,
+                                lambda line: f"UniProtKB:{line[1]}",  # subject id
+                                lambda line: f"UniProtKB:{line[2]}",  # object id
+                                lambda line: "biolink:phosphorylates",  # predicate
+                                lambda line: {}, #Node 1 props
+                                lambda line: {}, #Node 2 props
+                                lambda line: {
+                                                'phosphorylation_sites':line[3],
+                                                'primary_sources':line[4],
+                                                'secondary_sources':line[5]
+                                            }, #Edge props
+                                comment_character=None,
+                                delim=",",
+                                has_header_row=True
+                            )
+        return extractor.load_metadata