Metadata-Version: 1.1
Name: deepbgc
Version: 0.0.2
Summary: DeepBGC - Biosynthetic Gene Cluster detection and classification
Home-page: http://www.merck.com
Author: David Příhoda, Geoffrey Hannigan
Author-email: david.prihoda1@merck.com
License: MIT
Description: # DeepBGC: Biosynthetic Gene Cluster detection and classification.
        
        ## Install DeepBGC
        
        - Run `pip install deepbgc` to install the `deepbgc` python module.
        - **Note**: Tensorflow is not available for Python 3.7 ([link](https://github.com/tensorflow/tensorflow/issues/17022)) so please use Python 3.6 if you experience this issue.
        
        ## Prerequisities
        
        - Install Python 3.6 (version 3.7 is not supported by TensorFlow yet)
        - Install Prodigal and put the `prodigal` binary it on your PATH: https://github.com/hyattpd/Prodigal/releases
        - Install HMMER and put the `hmmscan` and `hmmpress` binaries on your PATH: http://hmmer.org/download.html
        - Download and **extract** Pfam database from: ftp://ftp.ebi.ac.uk/pub/databases/Pfam/releases/Pfam31.0/Pfam-A.hmm.gz
        
        ## Use DeepBGC
        
        ### Detection
        
        Detect BGCs in a genomic sequence.
        
        ```bash
        # Show detection help
        deepbgc detect --help
        
        # Detect BGCs in a nucleotide sequence
        deepbgc detect --model DeepBGCDetector_v0.0.1.pkl --pfam Pfam-A.hmm --output myCandidates/ myInputSequence.fa
        
        # Detect BGCs with >0.9 score in existing Pfam CSV sequence
        deepbgc detect --model myModel.pkl --output myStrictCandidates/ -s 0.9 myCandidates/myCandidates.pfam.csv
        
        ```
        
        ### Classification
        
        Classify BGCs into one or more classes.
        
        ```bash
        # Show classification help
        deepbgc classify --help
        
        # Predict biosynthetic class of detected BGCs
        deepbgc classify --model RandomForestMIBiGClasses_v0.0.1.pkl --output myCandidates/myCandidates.classes.csv myCandidates/myCandidates.candidates.csv
        
        ```
        
        ### Trained Models
        
        The trained model files can be found in the GitHub code release [here](https://github.com/Merck/deepbgc/releases).
        
Keywords: biosynthetic gene clusters,bgc detection,deep learning,pfam2vec
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python :: 3
