Databases (#64)

* removed comment * removed kinase_schema.CollectionKinaseInfo * comment on PRKD2 and AlphaMissense * temporary scratch for aligning sequences to DiscoverX
choderalab · Dec 3, 2024 · f3881ce · f3881ce
1 parent 04ea845
commit f3881ce
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Showing 5 changed files with 183 additions and 15 deletions.
diff --git a/missense_kinase_toolkit/databases/missense_kinase_toolkit/databases/kinase_schema.py b/missense_kinase_toolkit/databases/missense_kinase_toolkit/databases/kinase_schema.py
@@ -439,6 +439,7 @@ def create_kinase_models_from_df(
     if df is None:
         df = concatenate_source_dataframe()
 
+    # concatenate_source_dataframe could return None
     if df is None:
         logger.error("Dataframe is None. Cannot create kinase models.")
         return None

diff --git a/missense_kinase_toolkit/databases/missense_kinase_toolkit/databases/plot.py b/missense_kinase_toolkit/databases/missense_kinase_toolkit/databases/plot.py
@@ -125,7 +125,6 @@ def generate_alignment(self) -> None:
             text="text",
             text_align="center",
             text_color="black",
-            # text_font           = "monospace",
             text_font_size=f"{str(self.font_size)}pt",
         )
         rects = Rect(
@@ -150,9 +149,10 @@ def show_plot(self) -> None:
         """Show sequence alignment plot via Bokeh."""
         from bokeh.plotting import show
 
+        # show in separate window
+        show(self.plot)
+
         # notebook alternative
         # import panel as pn
         # pn.extension()
         # pn.pane.Bokeh(alignment_klifs_min.plot)
-
-        show(self.plot)
diff --git a/notebooks/databases.ipynb b/notebooks/databases.ipynb
@@ -977,9 +977,7 @@
     ")\n",
     "df_merge.to_csv(\"../data/kinhub_uniprot_merge.csv\", index=False)\n",
     "\n",
-    "dict_kin = kinase_schema.create_kinase_models_from_df(df_merge)\n",
-    "\n",
-    "model_kinase = kinase_schema.CollectionKinaseInfo(kinase_dict=dict_kin)"
+    "dict_kin = kinase_schema.create_kinase_models_from_df(df_merge)"
    ]
   }
  ],

diff --git a/notebooks/klifs_pocket.ipynb b/notebooks/klifs_pocket.ipynb
@@ -49,7 +49,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "id": "d01ab1c6-1d6e-465a-9f1e-e5462f0ac264",
    "metadata": {},
    "outputs": [],
@@ -63,7 +63,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "id": "cf9e691e-a7aa-4005-aece-ae6183323d4a",
    "metadata": {},
    "outputs": [],
@@ -342,6 +342,159 @@
     "dict_seq = {hgnc: \"\".join([*klifs_pocket.KLIFS2UniProtSeq.values()])\\\n",
     "            for hgnc, klifs_pocket in dict_klifs.items()}"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4411c6fd-0a18-4f1c-a83f-915da1f51d39",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "41f09832-087c-4856-adbe-d3fe90077a5c",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fbfc696b-8138-4491-a890-3713f63b75b8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import json\n",
+    "import glob"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "402fdb8c-433e-4750-b7f5-931b4baabb4c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for key, val in dict_kinase.items():\n",
+    "    with open(f\"../data/KinaseInfo/{key}.json\", \"w\") as outfile:   \n",
+    "        json.dump(val.json(), outfile)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "62c4675a-8fcf-42b9-b941-1cb908f539c8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "list_json = glob.glob(\"../data/KinaseInfo/*\")\n",
+    "\n",
+    "dict_import = {}\n",
+    "\n",
+    "for file in list_json:\n",
+    "    with open(file, \"r\") as openfile:\n",
+    "        json_obj = json.load(openfile)\n",
+    "        kinase_obj = kinase_schema.KinaseInfo.parse_raw(json_obj)\n",
+    "        dict_import[kinase_obj.hgnc_name] = kinase_obj\n",
+    "\n",
+    "dict_import = {key: dict_import[key] for key in sorted(dict_import.keys())}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "id": "f0d4c415-60a4-4cc3-a96e-8d6623ecb5e3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "temp = \"PFWKILNPLLERGTYYYFMGQQPGKVLGDQRRPSLPALHFIKGAGKKESSRHGGPHCNVFVEHEALQRPVASDFEPQGLSEAARWNSKENLLAGPSENDPNLFVALYDFVASGDNTLSITKGEKLRVLGYNHNGEWCEAQTKNGQGWVPSNYITPVNSLEKHSWYHGPVSRNAAEYLLSSGINGSFLVRESESSPGQRSISLRYEGRVYHYRINTASDGKLYVSSESRFNTLAELVHHHSTVADGLITTLHYPAPKRNKPTVYGVSPNYDKWEMERTDITMKHKLGGGQYGEVYEGVWKKYSLTVAVKTLKEDTMEVEEFLKEAAVMKEIKHPNLVQLLGVCTREPPFYIITEFMTYGNLLDYLRECNRQEVNAVVLLYMATQISSAMEYLEKKNFIHRDLAARNCLVGENHLVKVADFGLSRLMTGDTYTAHAGAKFPIKWTAPESLAYNKFSIKSDVWAFGVLLWEIATYGMSPYPGIDLSQVYELLEKDYRMERPEGCPEKVYELMRACWQWNPSDRPSFAEIHQAFETMFQESSISDEVEKELGKQGVRGAVSTLLQAPELPTKTRTSRRAAEHRDTTDVPEMPHSKGQGESDPLDHEPAVSPLLPRKERGPPEGGLNEDERLLPKDKKTNLFSALIKKKKKTAPTPPKRSSSFREMDGQPERRGAGEEEGRDISNGALAFTPLDTADPAKSPKPSNGAGVPNGALRESGGSGFRSPHLWKKSSTLTSSRLATGEEEGGGSSSKRFLRSCSASCVPHGAKDTEWRSVTLPRDLQSTGRQFDSSTFGGHKSEKPALPRKRAGENRSDQVTRGTVTPPPRLVKKNEEAADEVFKDIMESSPGSSPPNLTPKPLRRQVTVAPASGLPHKEEAGKGSALGTPAAAEPVTPTSKAGSGAPGGTSKGPAEESRVRRHKHSSESPGRDKGKLSRLKPAPPPPPAASAGKAGGKPSQSPSQEAAGEAVLGAKTKATSLVDAVNSDAAKPSQPGEGLKKPVLPATPKPQSAKPSGTPISPAPVPSTLPSASSALAGDQPSSTAFIPLISTRVSLRKTRQPPERIASGAITKGVVLDSTEALCLAISRNSEQMASHSAVLEAGKNLYTFCVSYVDSIQQMRNKFAFREAINKLENNLRELQICPATAGSGPAATQDFSKLLSSVKEISDIVQR\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "id": "bf5b5dc7-8ff4-404d-b656-6fc0b56a62da",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1167"
+      ]
+     },
+     "execution_count": 48,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(temp)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "id": "05475fe0-a66b-4bf8-968f-6521f9fcbf93",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1130"
+      ]
+     },
+     "execution_count": 49,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(dict_kinase[\"ABL1\"].UniProt.canonical_seq)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "id": "2885ec65-4ce5-47a9-8eae-84045c33e674",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "False"
+      ]
+     },
+     "execution_count": 50,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dict_kinase[\"ABL1\"].UniProt.canonical_seq in temp"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "id": "85f1a780-a747-4ca9-a170-be5e99509fd0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 43,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "\"VKEISDIVQ\" in dict_kinase[\"ABL1\"].UniProt.canonical_seq"
+   ]
   }
  ],
  "metadata": {

diff --git a/notebooks/pkis2_km_atp.ipynb b/notebooks/pkis2_km_atp.ipynb
@@ -214,6 +214,7 @@
     "                           if idx is not np.nan else np.nan for idx in list_concat]\n",
     "\n",
     "# manual fix\n",
+    "# cannot tell difference between PRKD2 using UniProt ID\n",
     "# df_pkis_copy.loc[df_pkis_copy[\"Assay Name\"] == \"PKD2\", \"uniprot\"] = \"Q13563\"\n",
     "df_pkis_copy.loc[df_pkis_copy[\"Assay Name\"] == \"PRKD2\", \"uniprot\"] = \"Q9BZL6\"\n",
     "df_pkis_copy.loc[df_pkis_copy[\"Assay Name\"] == \"RSK1\", \"uniprot\"] = \"Q15418\""
@@ -422,7 +423,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 15,
    "id": "ed5a72db-94be-4490-a90f-3d7af677955e",
    "metadata": {},
    "outputs": [],
@@ -464,7 +465,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 17,
    "id": "78c846e6-1ba0-4f55-99a4-aab09cda3108",
    "metadata": {},
    "outputs": [],
@@ -490,7 +491,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 18,
    "id": "206fbb7a-fa14-4c2a-bfe7-c39bfdde7f08",
    "metadata": {},
    "outputs": [
@@ -556,7 +557,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 19,
    "id": "f9e4593a-6d29-4c7c-932a-d4c95f182f87",
    "metadata": {},
    "outputs": [],
@@ -580,10 +581,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 20,
    "id": "0c487f05-a65a-474a-a544-b0e69236abc4",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "8a5c8d0b5df747e5b0373714f5fafe8a",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/684 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "dict_alphamissense = {i: {\"Score\": None, \"Class\": None} for i in \\\n",
     "                      df_klifs_mut_wt.loc[df_klifs_mut_wt[\"uniprot\"].apply(\n",
@@ -599,7 +615,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 117,
+   "execution_count": 21,
    "id": "4223aa00-a653-4e9d-858a-93a45070e007",
    "metadata": {},
    "outputs": [],