fix: multiple minor fixes#384
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WalkthroughThe changes update the Arriba tool version in the environment configuration, remove a post-deployment script that manually patched Arriba, update a meta wrapper version reference, specify a pandas dtype for a column in a sample file, and remove debug print statements from a Python script. Changes
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Actionable comments posted: 1
🧹 Nitpick comments (1)
workflow/envs/arriba.yaml (1)
5-5: Add missing newline at end of file.Static analysis detected that the file is missing a newline character at the end.
- - arriba =2.5 + - arriba =2.5 +
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📒 Files selected for processing (5)
workflow/envs/arriba.post-deploy.sh(0 hunks)workflow/envs/arriba.yaml(1 hunks)workflow/rules/common.smk(1 hunks)workflow/rules/fusion_calling.smk(1 hunks)workflow/scripts/split-call-tables.py(0 hunks)
💤 Files with no reviewable changes (2)
- workflow/scripts/split-call-tables.py
- workflow/envs/arriba.post-deploy.sh
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🧠 Learnings (1)
workflow/rules/common.smk (1)
Learnt from: johanneskoester
PR: snakemake-workflows/dna-seq-varlociraptor#346
File: workflow/rules/common.smk:122-135
Timestamp: 2024-12-13T08:46:33.627Z
Learning: In `workflow/rules/common.smk`, explicit error handling for reading TSV files (e.g., using `pd.read_csv`) is unnecessary when the files are specified in the configuration, as the configuration schema ensures their presence and correctness.
🪛 YAMLlint (1.37.1)
workflow/envs/arriba.yaml
[error] 5-5: no new line character at the end of file
(new-line-at-end-of-file)
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🔇 Additional comments (2)
workflow/envs/arriba.yaml (1)
5-5: LGTM! Version update aligns with PR objectives.The arriba version update from 2.4 to 2.5 is correct and consistent with the PR's goal of modernizing the fusion calling workflow.
workflow/rules/common.smk (1)
14-14: Excellent fix for the umi_len dtype issue!Adding
"umi_len": "Int64"to the dtype specification correctly addresses the issue where empty cells in the umi_len column were being interpreted as float type, causing invalid parameterization in fastp. The use of pandas' nullable integer type (Int64) is the appropriate solution for handling missing values in integer columns.
2 participants
This PR includes some minor fixes, changes and cleanups.
fix: When the column 'umi_len' has empty cells it automatically gets interpreted as float leading to an invalid parameterization of fastp. This has been fixed by setting the column to Int64.
change: We needed to apply a post-deploy script to the arriba environment in order to covert fusion calls to vcf record. The latest version of arriba includes that conversion script and there for the post-deploy script is not necessary anymore.
cleanup: removed a print command for debugging from split-call-tables.py
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