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Merge pull request #157 from umccr/dev
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alexiswl authored Oct 30, 2023
2 parents 0dbe35b + d79b80d commit 3828edc
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2 changes: 2 additions & 0 deletions Changelog.md
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Expand Up @@ -15,6 +15,8 @@ For changes in deployment, please see the [deployment changelog](deploy/cttso-ic

* Update sample type trimming of _sample suffix (https://github.com/umccr/cttso-ica-to-pieriandx/pull/150)
* Resolves https://github.com/umccr/cttso-ica-to-pieriandx/issues/149
* Update patient_care naming to patientcare (https://github.com/umccr/cttso-ica-to-pieriandx/pull/156)
* Resolves https://github.com/umccr/cttso-ica-to-pieriandx/issues/155

## 2023-10-18

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2 changes: 2 additions & 0 deletions deploy/cttso-ica-to-pieriandx-cdk/Changelog.md
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Expand Up @@ -13,6 +13,8 @@ are nested under deploy/cttso-ica-to-pieriandx-cdk.

* Dont resubmit deleted samples - also remove deleted samples from the lims sheet (https://github.com/umccr/cttso-ica-to-pieriandx/pull/151)
* Resolves https://github.com/umccr/cttso-ica-to-pieriandx/issues/146
* Use loc over iloc for pandas selection (https://github.com/umccr/cttso-ica-to-pieriandx/pull/154)
* Resolves https://github.com/umccr/cttso-ica-to-pieriandx/issues/153

## 2023-10-18

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Expand Up @@ -263,7 +263,7 @@ def get_libraries_for_processing(merged_df) -> pd.DataFrame:
logger.warning(f"Already run and deleted this combination {process_row['subject_id']} / {process_row['library_id']} / {process_row['portal_wfr_id']}, not reprocessing")

# Delete via index
to_process_df = to_process_df.iloc[list(
to_process_df = to_process_df.loc[list(
set(to_process_df.index.tolist()) - set(already_deleted_list_index)
)]

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6 changes: 5 additions & 1 deletion utils/accession.py
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Expand Up @@ -450,7 +450,11 @@ def sanitise_data_frame(input_df: pd.DataFrame) -> pd.DataFrame:
# Coerce patient care sample to patientcare
input_df["sample_type"] = input_df["sample_type"].apply(lambda x:
SampleType(
re.sub(r"_?sample$", "", x.lower().replace(" ", ""))
re.sub(
r"_?sample$",
"",
x.lower().replace(" ", "").replace("patient_care", "patientcare")
)
))
input_df["ethnicity"] = input_df["ethnicity"].apply(lambda x: Ethnicity(x.lower()))
input_df["race"] = input_df["race"].apply(lambda x: Race(x.lower()))
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