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AG-1117: Add new ensembl info fields to gene_info transform #95

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Nov 6, 2023
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AG-1117: Add new ensembl info fields to gene_info transform #95

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2 changes: 2 additions & 0 deletions config.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -156,6 +156,8 @@
meanlogcpm: mean
quartile3logcpm: third_quartile
maximumlogcpm: max
possible_replacement: ensembl_possible_replacements
permalink: ensembl_permalink
provenance:
- syn25953363.6
- syn12514826.4
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38 changes: 32 additions & 6 deletions src/agoradatatools/etl/transform/gene_info.py
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Expand Up @@ -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"],
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Note: changes like this are from the black formatter, I didn't change anything functional.

)

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(
Expand All @@ -97,6 +106,21 @@ def transform_gene_info(
axis=1,
)

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Real changes I made start here.

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

Expand All @@ -110,6 +134,7 @@ def transform_gene_info(
druggability,
biodomains,
tep_info,
ensembl_info,
]:
gene_info = pd.merge(
left=gene_info,
Expand Down Expand Up @@ -181,6 +206,7 @@ def transform_gene_info(
"is_adi",
"is_tep",
"resource_url",
"ensembl_info",
]
]

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2 changes: 2 additions & 0 deletions test_config.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -156,6 +156,8 @@
meanlogcpm: mean
quartile3logcpm: third_quartile
maximumlogcpm: max
possible_replacement: ensembl_possible_replacements
permalink: ensembl_permalink
provenance:
- syn25953363.6
- syn12514826.4
Expand Down
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