| # Task |
|
|
| I am analyzing a single-cell perturbation data set with the D-SPIN framework |
| (using the supplied source under `source/`). I trained a model and saved |
| the inferred perturbation response vectors to |
| `fixtures/public/model_responses.npz`; the sample metadata table — which |
| sample is a control, and which batch each sample belongs to — is in |
| `fixtures/public/sample_metadata.csv`. |
|
|
| Following the documented analysis workflow, I then computed each sample's |
| response relative to the control samples: every sample's relative response |
| is supposed to be its response vector minus the average response of the |
| control samples in the same batch, and samples in a batch without control |
| samples use the average over all control samples. |
|
|
| The results do not behave the way the definition says they should: |
|
|
| - the control samples' own relative responses are clearly not centered at |
| zero within their batch, so the baseline that was subtracted cannot be the |
| batch's control average; |
| - when I reorder the rows of the metadata table and rerun the analysis, the |
| relative response assigned to the same sample changes, even though nothing |
| about the samples themselves changed. |
|
|
| You can reproduce both observations with: |
|
|
| ```bash |
| python reproduce.py |
| ``` |
|
|
| See `reproduction.md` for the report contract. |
|
|
| Please inspect the source and public workflow, figure out |
| why the computed relative responses disagree with their definition, and |
| repair the implementation so that the analysis conforms to the documented |
| definition for all valid inputs — any saved response matrix and any sample |
| metadata table a user could legitimately provide. Do not hard-code specific |
| sample identities, batch layouts, orderings, or expected outputs. |
|
|
