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…t transformation in PDAC landing page
…nt and locking mechanisms
… to prevent downstream errors
… too many arguments
… characters in length rather than 8
…agged columns for review
…rization and sanitization before upload
…ation and enhance user experience during uploads
…lyAmbiguousObsColumns function
…a-is-categorical-or-numerical-before-upload 229 indicate if observation metadata is categorical or numerical before upload
| raise e No newline at end of file | ||
| table_path = self.zarr_path / "tables" / "table" | ||
| import anndata | ||
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| questionable = flag_ambiguous_obs_columns(adata.obs) | ||
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| metadata_file = self.staging_area / 'metadata.json' | ||
| with open(metadata_file, 'r') as f: |
| # can skip straight past that step. | ||
| metadata['obs_dtype_reviewed'] = not bool(questionable) | ||
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| with open(metadata_file, 'w') as f: |
…ed in path expression' Co-authored-by: Copilot Autofix powered by AI <62310815+github-advanced-security[bot]@users.noreply.github.com>
…ed in path expression' Co-authored-by: Copilot Autofix powered by AI <62310815+github-advanced-security[bot]@users.noreply.github.com>
…ed in path expression' Co-authored-by: Copilot Autofix powered by AI <62310815+github-advanced-security[bot]@users.noreply.github.com>
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This pull request introduces several improvements and fixes across the codebase, focusing on standardizing and validating observation metadata, improving resource management for consumers, and enhancing spatial data handling. The most important changes are outlined below.
Observation Metadata Standardization and Validation
anndata_processor.pywith a new_sanitize_and_flag_obs_columnsmethod. This method standardizes and sanitizes theobstable, flags ambiguous columns (e.g., numeric columns that may be categorical), and records them inmetadata.jsonfor uploader review. The new logic is consistently applied across all supported data formats, improving downstream data quality and user experience. [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12]Resource Management and Reliability
projectr-consumer, improving reliability and stability of the system.Spatial Data Handling Improvements
zarr_pathproperty to theSpatialHandlerclass, with getter and setter, to consistently manage the Zarr file path. Updated theget_adatamethod inanalysis.pyto load AnnData directly from the Zarr file, improving reliability and error handling. [1] [2] [3]adata.varare made unique before downstream analysis in both the primary analysis pipeline and spatial data QC/embedding computation, preventing errors caused by duplicate IDs. [1] [2]Dependency and Documentation Updates
kaleidodependency from requirements and installation scripts. [1] [2]These changes collectively improve data integrity, reliability, and maintainability of the system.