How to quantify evidence of co-functionality?
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- Dominant language
- R
- Stars
- 14
- Forks
- 1
- PR merge metrics
- No merged PRs in 30d
Description
From [Bioinformatics](https://bioinformatics.stackexchange.com/q/7051/48):
"quantify how likely two genes are correlated in their enrichment, function etc. For example, using STRING we can see that PIK3CA and PTEN are more co-functioning than PIK3CA and SF3B1. "
The question is how to add this higher co-functioning evidence in BioCor? My answer is that this should be two separate metrics.
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
No file, test, or entry point is named. Start by defining the two separate co-functionality metrics proposed in the issue and determining how they should fit BioCor's existing functional-similarity calculations. Done means the metric definitions and implementation scope are agreed.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- r
- Domain
- bioinformatics
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100