Different results with the same dependencies
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Description
I am having a problem, where I can't reproduce the results of a single factor analysis, due to different results obtained by the DeseqStats function. The obtained LFC are slightly different in two separate conda environments.
Both environments run on the same machine and have following dependencies:
Python: 3.10
pydeseq2: 0.4.1
and the dependencies used by pydeseq2 are in both environments:
anndata: 0.8.0
statsmodels: 0.13.5
numpy: 1.24.4
pandas: 2.0.0
scikit-learn: 1.2.2
scipy: 1.10.1
Do you have an idea, where this difference could come from?
thanks
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the linked DeseqStats documentation and compare the two conda environments, including the listed Python, PyDESeq2, and dependency versions. Done means identifying why the same single-factor analysis produces different LFC values and documenting a reproducible cause or resolution.
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Assessment
- Tech stack
- numpy, pandas, python, scikit-learn
- Domain
- bioinformatics
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100