Comments (1)
We take care of this by careful benchmarking.
Otherwise there's nothing one can do.
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Related Issues (20)
- Why do large networks (>=200 nodes) only produce results when sparse in DCE reconstruction benchmarking? HOT 1
- Helpful links HOT 1
- `glm.nb` throws warnings and errors when data is naughty HOT 3
- How to include library size in the model? HOT 6
- Using causal effects as edge weights can be misleading HOT 3
- Simulating negative binomial read counts on DAGs HOT 5
- How to choose the "correct" link function? HOT 4
- Input DAGs may not satisfy faithfulness assumption HOT 1
- Compare multiple performance measurements in benchmarking HOT 1
- How to validate (real data) biological results? HOT 2
- How to benchmark perturbed ground truth? HOT 1
- How to control the noise in (large) graphs? HOT 1
- List of relevant pathway enrichment tools HOT 6
- Open issues: HOT 3
- TPM vs raw counts HOT 1
- Merge pathway nodes HOT 1
- Random DAG creation
- bug in generating graph? HOT 5
- Feature: add arbitrary distribution choice to simulate data HOT 2
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