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PGPg_finder

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PGPg_finder is a command-line tool that offers different workflows for genome and metagenome annotation of Plant-Growth Promotion Genes. It's designed to be flexible and easy to use pipeline, with several pre-configured workflows to choose from based on the tools and steps you need.

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# PGPg_finder
![My Image](https://raw.githubusercontent.com/tpellegrinetti/PGPg_finder/main/README/logo.png)
PGPg Finder is a versatile command-line tool designed for the annotation of Plant-Growth Promotion Traits (PGPT) in both genomes and metagenomes. Rooted in the comprehensive PLant-associated BActeria web resource database (PLaBAse), this tool boasts flexibility and user-friendliness. PGPg Finder offers a range of pre-configured workflows, enabling users to select the tools and processes best suited to their specific research needs.

# Features
The pipeline allows you to choose from several workflows based on the tools and steps you need. The workflows currently available are:

## Genome Analysis
**genome_wf:** A genome annotation pipeline that uses Prodigal for gene prediction and DiAMOND against PLaBAse.

## Metagenome Analysis
**meta_wf:** A metagenome workflow with megahit assembly, Prodigal gene prediction, DIAMOND annotation, Bowtie2 mapping, samtools quantification.

**metafast_wf:** A metagenome workflow with PEAR assembly and direct DIAMOND annotation.

Each workflow is designed to be run with a specific set of input files and produces a set of output files. The tool also supports running on multiple threads to improve performance.

We plan to add more functionalities and workflows in future versions. If you need a specific feature, you are welcome to open an issue or submit a pull request.

# Installation:

To use the tool, you first need to clone the repository and ensure that all dependencies are installed.
```bash
git clone https://github.com/tpellegrinetti/PGPg_finder/
```
After this procedure, you need to performe the installation of dependancies with conda (recomended).
The conda will create a separated environment called PGPg_finder.
```bash
bash install.sh
```
If conda not work for you, you can install the dependences mannualy without a separeted environment and run PGPg_finder (not recomended).

# Usage:

if you want to learn how to use the PGPg_finder in a detailed way, click the link below:

[Tutorial](https://github.com/tpellegrinetti/PGPg_finder/blob/main/Tutorial.md)

You can check the available commands in PGPg_finder by running:
`python PGPg_finder.py -h` After that, you need to choose one of the available workflows.

You can run the PGPg_finder tool using the following command:

`python PGPg_finder.py -w workflow -i input_directory -o output_directory -t threads`

the -a argument is optional and works if you want to provide assembly files

1) Running PGPg_finder with GENOMES or MAGs:

`python PGPg_finder.py -w genome_wf -i /path/to/fasta/folder/ -o /path/to/your/desired/out/ -t 12`

2) Running PGPg_finder with METAGENOMES:
 
a) Fast way (less accurated)

`python PGPg_finder.py -w metafast_wf -i /path/to/fasta/folder -o /path/to/your/desired/out/ -t 12`

b) Slow way (more accurated)

`python PGPg_finder.py -w meta_wf -i /path/to/fasta/folder -o /path/to/your/desired/out/ -t 12`

Here you can provide your metagenome assemblies with -a option

### For help with the arguments, you can use the command python PGPb_finder -h. ###

# Dependencies
This tool depends on the following libraries and tools:

* Python 3.7.12
* Bash
* Trimmomatic==0.39
* pear==0.9.6
* Diamond==2.0.14
* Megahit==1.2.9
* Prodigal==2.6.3
* Bowtie2=2.3.5.1
* BBmap==39.01
* Samtools==1.17
* Seaborn==0.12.2
* Scipy==1.7.3
* gawk==5.1.0
* matplotlib==3.3.2
* numpy==1.21.6
* pandas=1.3.5

# Database PLaBAse
Please, note that this pipeline was developed based on a curated database called "PLant-associated BActeria web resource (PLaBAse)".
Acess PLaBAse website: https://plabase.cs.uni-tuebingen.de/

We encourage you to cite the PLaBAse:

Patz S, Rauh M, Gautam A, Huson DH. mgPGPT: Metagenomic analysis of plant growth-promoting traits.(submitted, 2024, preprint)

Patz S, Gautam A, Becker M, Ruppel S, Rodríguez-Palenzuela P, Huson DH. PLaBAse: A comprehensive web resource for analyzing the plant growth-promoting potential of plant-associated bacteria. (submitted 2021, preprint)

If PGPg_finder was useful for you please cite us:

Pellegrinetti, TA; Monteiro, G; Lemos, LN; RAC, Santos; Barros, A; Mendes, L. (2024) PGPg_finder: A Comprehensive and User-friendly Pipeline for Identifying Plant Growth-Promoting Genes in Genomic and Metagenomic Data. Rhizosphere.

# Issues in Database Downloading
PGPg_finder relies on databases from PLaBaSe, which may be temporarily unavailable at certain times. If you experience issues downloading the databases through install.sh, you can download them manually from the links below.

PGPT_BASE_nr (For genomes):
https://plabase.cs.uni-tuebingen.de/pb/tools/PGPTblhm/data/factors/PGPT_BASE_nr_Aug2021n_ul_1.fasta.gz

mgPGPT-db (For metagenomes)
https://plabase.cs.uni-tuebingen.de/pb/tools/PGPTblhm/data/factors/mgPGPT/mgPGPT-db_Feb2022_ul_dwnld.fasta.gz

If this links is not working you can alternative use this links:
Download the following folder:

`https://unitc-my.sharepoint.com/:f:/g/personal/iijag01_cloud_uni-tuebingen_de/IgD-z6ZxAOzKSqoe_KS4yGhaAZGXBp3bG1sJO9sy8OvCXfM?e=TsC7sI`

PGPT_BASE_nr: PGPT_BASE_nr_Aug2021n_ul_1.fasta.gz
mgPGPT-db: mgPGPT-db_Feb2022_ul_dwnld.fasta.gz

Place these files in the database folder of PGPg_finder and run the following commands:
```
diamond makedb --in PGPT_BASE_nr_Aug2021n_ul_1.fasta.gz --db genome
diamond makedb --in mgPGPT-db_Feb2022_ul_dwnld.fasta.gz --db metagenome
```

You will get two .dmnd files. If desired, you can remove the .fasta.gz files

# Contact for more information
If you have problems to download the PLaBAse database, or any other installation issues, please contact us.

For dedicated support with running PGPg_finder, please contact: tpellegrinetti@usp.br

PGPg_finder

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