Metadata-Version: 2.2
Name: combgc
Version: 0.6.4
Summary: A tool that aggregates, filters and combines the results of BGC prediction tools: antiSMASH, deepBGC, and GECCO.
Author-email: Tom Richtermeier <tom.richtermeier@gmx.de>, Jasmin Frangenberg <jasmin.frangenberg@example.com>
Maintainer-email: Tom Richtermeier <tom.richtermeier@gmx.de>, Jasmin Frangenberg <jasmin.frangenberg@example.com>, Anan Ibrahim <ananhamido@hotmail.com>
License: MIT License
        
        Copyright (c) 2024 Tom Richtermeier, Jasmin Frangenberg
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.
Project-URL: Homepage, https://github.com/tomrichtermeier/comBGC-Filter/tree/main
Project-URL: Issues, https://github.com/tomrichtermeier/comBGC-Filter/issues
Project-URL: Source, https://github.com/tomrichtermeier/comBGC-Filter
Keywords: biosynthetic-gene-clusters,bioinformatics,genes,bgc
Classifier: Programming Language :: Python :: 3.12
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: biopython>=1.79
Requires-Dist: pandas>=1.0

# comBGC
<img src="../images/com-bgc-logo.png" alt="Werner Siemens Foundation" width="250" />

comBGC is a tool that can be used to combine the results of the prediction tools deepBGC, GECCO, and antiSMASH for detecting bionsynthetic gene clusters (BGCs). It combines the results of all three tools and adds different filters, so only hight quality BGCs are included. Furthermore, a merging step is applied to the datasets. This removes the redundancy and combines the results of the prediction tool. This way no duplicate BGCs are included in the final table.
### Installation
---
To use comBGC, you first need to create an environment using **conda**:
    
    conda create -n combgc

Activate the environment

    conda activate combgc

and install the required packages using **pip**

    pip install -r requirements.txt

### Using comBGC
---
To run comBGC and parse the results of multiple BGC prediction tools into a single table you need to specify diffent parameters which can be displayed with using `-h` :

    python3 combgc/comBGC.py --help

Using --helpt gives you an overview of all parameters that can be modified, of which `-i`, `-o`, and `--cores` are required.

    comBGC arguments:
        -h, --help              
        -i [PATH(s) [PATH(s) ...]], --input [PATH(s) [PATH(s) ...]] # required
        -o [PATH], --outdir [PATH]                                  # required
        -a [PATH], --antismash_multiple_samples [PATH] 
        -vv, --verbose          
        -v, --version           
        --cores [CORES]                                             # required
        --min_length [LENGTH]   
        --contig_edge [BASES]   
        --sample_metadata [PATH]
        --contig_metadata

- `-o, --outdir`
- `-i, --input` path(s) to the required output file(s) of antiSMASH, DeepBGC and/or GECCO
                these can be:  
                    - antiSMASH: <sample name>.gbk and (optional) knownclusterblast/ directory  
                    - DeepBGC:   <sample name>.bgc.tsv  
                    - GECCO:     <sample name>.clusters.tsv  
                Note: Please provide files from a single sample only. If you would like to
                summarize multiple samples, please see the --antismash_multiple_samples flag.
- `-o, --outdir` directory for comBGC output. Default: current directory
- `-a, --antismash_multiple_samples` directory of antiSMASH output. Should contain subfolders (one per
                                sample). Can only be used if --input is not specified.
- `-vv, --verbose` increase output verbosity
- `-v, --version` show version number and exit
- `--cores` number of CPU cores to use
- `--min_length` Minimum length [bp] of BGC sequence to keep. Default: 3000 bp
- `--contig_edge` Exclude BGCs within X bases on the contig edge. Default: 2 bp
- `--sample_metadata` Path to a TSV file containing sample metadata, 
                                e.g., 'path/to/sample_metadata.tsv'. The metadata table must have sample names 
                                in the first column and  contig IDs in the second column.
- `--contig_metadata` Path to a TSV file containing contig metadata, 
                                e.g., 'path/to/contig_metadata.tsv'. The metadata table must have sample names 
                                in the first column and  contig IDs in the second column.


**Example Usage**

    python3 combgc/comBGC.py \
    -i tests/antismash_example/ECO010-megahit/ECO010-megahit.gbk \
    tests/deepbgc_example/ECO010-megahit/ECO010-megahit.bgc.tsv \
    tests/gecco_example/ECO010-megahit/ECO010-megahit.clusters.tsv \
    -o ./output/ --cores 10


### Authors
---
This tool was initiated by Jasmin Frangenberg (@jasmezz) and expanded by Tom Richtermeier (@tomrichtermeier), while being supervised by Anan Ibrahim (@Darcy220606)

### Funding
---
This project was funded by Werner Siemens Foundation grant ‘Palaeobiotechnology’

<img src="../images/wss.svg" alt="Werner Siemens Foundation" width="250" />

