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Added custom models as submodule, added pipleline for trap species handling (up to alignment). Initial progress on custom model rules

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Tom Kasper
2026-10-03 15:16:36 +01:00
parent 3b93ceaf6e
commit f0cd594148
17 changed files with 270 additions and 21 deletions
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README.md
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@@ -15,12 +15,16 @@
- python 3.14
- snakemake
- python-dotenv
## Optional:
- custom-models package: live in a separate repo (`git@git.tk-ai.eu:Tom/eDNA_Stream_E01_custom_models.git`) included here as the `custom_models` git submodule; the workflow pip-installs it from that checkout (see `workflow/envs/torch_*.yaml`)
- clone with: `git clone --recurse-submodules ...` (or `git submodule update --init` on an existing clone)
- update to a newer version: `git submodule update --remote custom_models`, then commit the new pinned commit
- .env file with NCBI API key -> slightly speeds up reference fasta download
## Running:
```bash
cd workflow
snakemake --cores <cores> --resources gpu=<n_gpus>
```
snakemake --cores <cores> --resources gpu=<n_gpus> --use-conda
```
## Notes:
- Reads aligned to the FP traps by minimap are excluded for training -> esp. the E. coli reads are highly represented and should not be there, but are stable even when only using stringent alignment