sokrypton / sokrypton/ColabFold
Proper arguments for local MSA generation
Nobody has claimed this yet.
- Dominant language
- Jupyter Notebook
- Stars
- 2.9k
- Forks
- 747
- PR merge metrics
- No merged PRs in 30d
Description
Hi,
Thanks for your great program.
I want to locally generate MSAs for my proteins to predict how they interact (with AlphaPullDown).
I was wondering what are the correct parameters to choose for high quality MSA generation?
More specifically, should I use "colabfold_envdb" too? I realized if we want to use env_db, first a profile is created by searching against uniref, and later the profile is searched against the envdb. So, I expected that bfd.mgnify30.metaeuk30.smag30.a3m files would be larger than uniref.a3m ones, while I see the opposite. Why it happens?
Thanks in advance
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 locating the local MSA-generation documentation or command entry point, then review the parameters for env_db, colabfold_envdb, uniref, and the other databases mentioned. Done means documenting the appropriate parameters and explaining why the generated alignment files differ in size.
Written by the indexing model from the issue text.
Assessment
- Domain
- bioinformatics, databases
- Issue type
- Documentation
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100