140 automated e2e tests #143
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| """Calculate metrics.""" | ||
| df = self._data_store["stat.tsv"] | ||
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| for col in ["proteins", "precursors", "ms1_accuracy", "fwhm_rt"]: |
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this is a naming issue on alphaDIAs side. proteins and genes refers to values annotated in the library. pg is the column for proteins after fdr correction and with the correct inference mode.
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hm, not sure what you mean .. I read these values off the actual alphaDIA output?
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This is only about the implementation of the metric. AlphaDIA generates the pg column for FDR corrected protein groups. So for counting PGs at 1% FDR you would need to use the pg column.
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ah, I see .. given the metrics are only a placeholder for now, I would leave it like this
tests/e2e_tests/prepare_test_data.py
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| CONFIG_SOURCE_PATH = "../../alphadia/constants/default.yaml" | ||
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| def _download_file(url: str, target_name: str) -> None: |
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There is some overlap with alphadia.testing. I think we could unify this.
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First working version of end 2 end tests.
For each test case defined in a
yamlfile, download the test data, run alphadia, calculate metrics, and push them to neptune.Can be seen in action here: https://github.com/MannLabs/alphadia/actions/runs/9113110942/job/25053809668
On neptune:
Next steps: