[Question] How can I use precomputed genes via GFF format with DeepBGC?
Nobody has claimed this yet.
Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 25/100
- Issue type
- Feature
- Clarity
- Mostly clear
- Activity status
- Stale
- Tech stack
- python
- Domain
- bioinformatics
Research direction
Start by reviewing DeepBGC's command-line input handling and how it invokes Pyrodigal. Determine whether precomputed gene models in GFF can be supplied for the 50k genomes; done means documenting a working command or defining the required future support if it is not currently possible.
Written by the indexing model from the issue text.
Description
I have already run Pyrodigal on ~50k genomes and would like to run DeepBGC on these genomes without rerunning Pyrodigal in the backend. Is there similar usage to antiSMASH where precompute gene models can be provided via GFF? If so, what command can I run? If not, would this be in scope to add in a future update?
- Dominant language
- Jupyter Notebook
- Stars
- 161
- Forks
- 29
- PR merge metrics
- No merged PRs in 30d
Contributor guide
No contributing guide indexed for this repository
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.
More from Merck/deepbgc
-
Difficulty 4/5 3-5 days Newbie friendliness 25/100
-
why not plant? Open
Difficulty 5/5 Over a week Newbie friendliness 15/100
-
Difficulty 4/5 3-5 days Newbie friendliness 25/100
-
installing deepbgc Open
Difficulty 3/5 1-2 days Newbie friendliness 25/100
-
Difficulty 3/5 1-2 days Newbie friendliness 35/100
Similar issues
-
Difficulty 2/5 1-3 hours Newbie friendliness 72/100
-
Difficulty 2/5 1-3 hours Newbie friendliness 72/100
-
bug
Difficulty 2/5 1-3 hours Newbie friendliness 76/100
EBI-Metagenomics/mgnifams#62 ·
-
Difficulty 2/5 Half a day Newbie friendliness 68/100
-
Difficulty 2/5 1-3 hours Newbie friendliness 88/100