Comments (5)
Dear @LucaBertoli ,
Thank you for your interest in AbSplice. SpliceAI tends to take significant amount of time to run. To speed it up, we provide the fast lookup interface spliceai_rocksdb that uses precomputed SpliceAI scores. You can enable it by simply changing the field use_rocksdb
in the config file to True
and running Snakemake with --use-conda
option. It will create a conda environment and download the precomputed SpliceAI scores (it will take some time – about 1 hour and use approximately 180GB of storage). This should then significantly speed up the computation.
Let me know if you need any further assistance on that.
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Thanks for the answer.
What would be the difference with respect to using SpliceAI without precomputed scores?
What variants are present in the precomputed scores?
from absplice.
The precomputed scores contain all SNVs and indels up to 4 nucleotides. During the execution of the pipeline, scores for the variants present in the precomputed scores will be simply retrieved from the database. If the variant is not in the precomputed scores, it will be computed by running SpliceAI.
from absplice.
ok, so the output will be basically the same as running spliceAI from scratch, correct?
from absplice.
Yes, we do not skip variants that are not in the precomputed scores
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Related Issues (16)
- Add AbSplice to environment.yaml
- Convert EBM model to ONNX to get rid of interpret dependency HOT 3
- Can't get attribute 'EBMPreprocessor' on <module 'interpret.glassbox.ebm.ebm' HOT 2
- Add SpliceMap info to AbSplice output
- Bugs in Absplice implementation HOT 18
- Absplice-RNA HOT 3
- T2T CHM13v2.0 (hs1) support HOT 1
- can't install, stop at "Solving environment: |" HOT 2
- How to add specific tissues like the retina into the source code HOT 7
- Container Environment problem HOT 2
- How to get CATs data HOT 7
- Splicemap_tissues HOT 3
- License HOT 1
- Can't find cause of the error HOT 2
- Numpy Error appears in Example-Workflow-Execution HOT 2
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