| # Complete robust topic-to-cistrome binarization |
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|
| The included pycisTopic source can turn topic distributions attached to a full |
| cisTopic model into selected cell or region sets. A downstream workflow now |
| needs to consume probability matrices exported independently from topic-model |
| training and produce the discrete topic sets used for motif enrichment and |
| cistrome construction. |
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|
| The current source does not complete that workflow reliably. The public |
| reproduction exercises both region-topic and cell-topic inputs, including |
| zero-heavy probabilities at the precision used by exported matrices. It reports |
| that the required topic sets or portable output artifacts cannot be produced |
| consistently. |
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|
| Inspect the source snapshot and fixtures, and complete the |
| scientific capability so that independent topic-probability matrices can be |
| validated, optionally smoothed, thresholded, ranked and exported without a full |
| in-memory cisTopic object. |
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|
| Requirements: |
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|
| - support matrices whose rows are named cells or genomic regions and whose |
| columns are topics; |
| - preserve name-to-score alignment and deterministic descending ranking; |
| - support top-n selection and the histogram-based thresholding methods already |
| documented by the source; |
| - remain numerically finite for zero-heavy `float32` topic probabilities; |
| - treat constant topics as having no separable evidence rather than selecting |
| every row because of a histogram artifact; |
| - reject duplicate names, non-finite values, invalid `ntop` bounds and malformed |
| genomic intervals; |
| - produce the required portable downstream artifacts, including |
| deterministic threshold tables, cell tables and BED-compatible region tables; |
| - retain the existing object-based entry point where practical; |
| - do not hard-code the public names, topic count, matrix shape or expected |
| selected sets. |
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|
| Run the public workflow with: |
|
|
| ```bash |
| python reproduce.py |
| ``` |
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| The benchmark runs offline. Generated files belong under `outputs/`. |
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|
