From eee41138ae65f6cfa369c10f28668e03b84d1296 Mon Sep 17 00:00:00 2001
From: Jaclyn Beck <jaclyn.beck@sagebase.org>
Date: Fri, 3 Nov 2023 15:12:09 -0700
Subject: [PATCH] Added new ensembl info fields to gene_info transform

---
 config.yaml                                   |  2 +
 src/agoradatatools/etl/transform/gene_info.py | 38 ++++++++++++++++---
 test_config.yaml                              |  2 +
 3 files changed, 36 insertions(+), 6 deletions(-)

diff --git a/config.yaml b/config.yaml
index 1072ae16..a769caf6 100644
--- a/config.yaml
+++ b/config.yaml
@@ -156,6 +156,8 @@
           meanlogcpm: mean
           quartile3logcpm: third_quartile
           maximumlogcpm: max
+          possible_replacement: ensembl_possible_replacements
+          permalink: ensembl_permalink
         provenance:
           - syn25953363.6
           - syn12514826.4
diff --git a/src/agoradatatools/etl/transform/gene_info.py b/src/agoradatatools/etl/transform/gene_info.py
index 1dd9bcac..bf50fbfc 100644
--- a/src/agoradatatools/etl/transform/gene_info.py
+++ b/src/agoradatatools/etl/transform/gene_info.py
@@ -61,33 +61,42 @@ def transform_gene_info(
     druggability = druggability[useful_columns]
 
     target_list = nest_fields(
-        df=target_list, grouping="ensembl_gene_id", new_column="target_nominations", drop_columns=["ensembl_gene_id"]
+        df=target_list,
+        grouping="ensembl_gene_id",
+        new_column="target_nominations",
+        drop_columns=["ensembl_gene_id"],
     )
 
     median_expression = nest_fields(
-        df=median_expression, grouping="ensembl_gene_id", new_column="median_expression", drop_columns=["ensembl_gene_id"]
+        df=median_expression,
+        grouping="ensembl_gene_id",
+        new_column="median_expression",
+        drop_columns=["ensembl_gene_id"],
     )
 
     druggability = nest_fields(
-        df=druggability, grouping="ensembl_gene_id", new_column="druggability", drop_columns=["ensembl_gene_id"]
+        df=druggability,
+        grouping="ensembl_gene_id",
+        new_column="druggability",
+        drop_columns=["ensembl_gene_id"],
     )
 
     biodomains = (
         biodomains.groupby("ensembl_gene_id")["biodomain"]
-        .apply(set) # ensure unique biodomain names
+        .apply(set)  # ensure unique biodomain names
         .apply(list)
         .reset_index()
         .rename(columns={"biodomain": "biodomains"})
     )
 
     # sort biodomains list alphabetically
-    biodomains['biodomains'] = biodomains['biodomains'].apply(sorted)
+    biodomains["biodomains"] = biodomains["biodomains"].apply(sorted)
 
     # For genes with either is_adi or is_tep set to True, create a resource URL that opens
     # the portal page to the specific gene. This must be done using the hgnc_symbol from the
     # tep_info file and not the symbol in gene_info, because there are some mismatches
     # between the two and the hgnc_symbol from tep_info is the correct one to use here.
-    # resource_url should be NA if both is_adi and is_tep are false. 
+    # resource_url should be NA if both is_adi and is_tep are false.
     resource_url_prefix = "https://adknowledgeportal.synapse.org/Explore/Target%20Enabling%20Resources?QueryWrapper0=%7B%22sql%22%3A%22select%20*%20from%20syn26146692%20WHERE%20%60isPublic%60%20%3D%20true%22%2C%22limit%22%3A25%2C%22offset%22%3A0%2C%22selectedFacets%22%3A%5B%7B%22concreteType%22%3A%22org.sagebionetworks.repo.model.table.FacetColumnValuesRequest%22%2C%22columnName%22%3A%22target%22%2C%22facetValues%22%3A%5B%22"
     resource_url_suffix = "%22%5D%7D%5D%7D"
     tep_info["resource_url"] = tep_info.apply(
@@ -97,6 +106,21 @@ def transform_gene_info(
         axis=1,
     )
 
+    ensembl_info = gene_metadata[
+        [
+            "ensembl_gene_id",
+            "ensembl_release",
+            "ensembl_possible_replacements",
+            "ensembl_permalink",
+        ]
+    ]
+    ensembl_info = nest_fields(
+        df=ensembl_info,
+        grouping="ensembl_gene_id",
+        new_column="ensembl_info",
+        drop_columns=["ensembl_gene_id"],
+    )
+
     # Merge all the datasets
     gene_info = gene_metadata
 
@@ -110,6 +134,7 @@ def transform_gene_info(
         druggability,
         biodomains,
         tep_info,
+        ensembl_info,
     ]:
         gene_info = pd.merge(
             left=gene_info,
@@ -181,6 +206,7 @@ def transform_gene_info(
             "is_adi",
             "is_tep",
             "resource_url",
+            "ensembl_info",
         ]
     ]
 
diff --git a/test_config.yaml b/test_config.yaml
index 61908f20..c83afdbf 100644
--- a/test_config.yaml
+++ b/test_config.yaml
@@ -156,6 +156,8 @@
           meanlogcpm: mean
           quartile3logcpm: third_quartile
           maximumlogcpm: max
+          possible_replacement: ensembl_possible_replacements
+          permalink: ensembl_permalink
         provenance:
           - syn25953363.6
           - syn12514826.4