Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Inconsistency of IO files when running colabfold_search and colabfold_batch with templates locally #628

Open
petaripenev opened this issue Jun 12, 2024 · 1 comment

Comments

@petaripenev
Copy link

Expected Behavior

If one is to use the input option of colabfold_batch for a folder of a3m files with --template argument, the argument --pdb-hit-file should accept a folder with m8 files. Prediction should be done for each a3m and m8 pair, based on names for example.
Alternatively, the default behavior of --templates should be to look for .m8 files with the same name as the .a3m in the a3m input folder, since this is the way colabfold_search outputs its results. If such a file is missing then it should trigger an online search.

Current Behavior

The argument --pdb-hit-file of colabfold_batch can only be a file, therefore one has to run the command for each each alignment separately, which renders the batch in colabfold_batch moot.
If one submits a concatenated m8 file with all template hits, the prediction for each a3m alignment will use all templates listed in the file, regardless of the first column names used.

Context

I'm working on separating the alignment step from the modelling on our server so that we don't swamp our GPU nodes.

Your Environment

ColabFold v1.5.5
Ubuntu 22.04.4 LTS
cuda_12.3.r12.3

@petaripenev petaripenev changed the title Inconsistency on IO files when running colabfold_search and colabfold_batch with templates locally Inconsistency of IO files when running colabfold_search and colabfold_batch with templates locally Jun 12, 2024
@petaripenev
Copy link
Author

From reading the open pull requests it seems like this might fix it:
alexpBCR:colabfold-refactoring
And adds a very convenient option to split large number of files into smaller batches.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

1 participant