AMPcombi : Antimicorbial peptides parsing and functional classification tool

This tool parses the results of amp prediction tools into a single table and aligns the hits against a reference database of antimicrobial peptides for functional classifications.

For parsing: AMpcombi is developed to parse the output of these amp prediction tools:

For classification: AMPcombi is developed to offer functional annotation of the detcted AMPs by alignemnt to AMP reference databases, for e.g.,:

Alignment to the reference database is done using diamond blastp v.2.0.15

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Installation

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To install AMPcombi:

Add dependencies of the tool; python > 3.0, biopython, pandas and diamond. Installation can be done using:

• pip installation

pip install AMPcombi

• git repository

git clone https://github.com/Darcy220606/AMPcombi.git

• conda

conda env create -f ampcombi/environment.yml

or

 conda install AMPcombi

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Usage:

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There are two basic commands to run AMPcombi:

1. Using --amp_results

ampcombi --amp_results path/to/my/result_folder/

Here the head folder containing output files has to be given. AMPcombi finds and summarizes the output files from different tools, if the folder is structured and named as: /result_folder/toolsubdir/samplesubdir/sample.tool.filetype.

• Note that the filetype ending might vary and can be specified with --tooldict, if it is different from the default.

amp_results/
├── tool_1/
|   ├── sample_1/
|   |   └── sample_1.tool_1.tsv
|   └── sample_2/
|   |   └── sample_2.tool_1.tsv
├── tool_2/
|   ├── sample_1/
|   |   └── sample_1.tool_2.txt
|   └── sample_2/
|   |   └── sample_2.tool_2.txt
├── tool_3/
    ├── sample_1/
    |   └── sample_1.tool_3.predict
    └── sample_2/
        └── sample_2.tool_3.predict

2. Using --path_list and --sample_list

ampcombi --path_list [[list of paths to sample_1-outputs][list of paths to sample_2-outputs]] --sample_list [sample_1, sample_2] 

Here the paths to the output-files to be summarized can be given as a list for each sample. Together with this option a list of sample-names has to be supplied.

Input options:

• Note: The fasta file corresponding to the AMP database should not contain any characters other than ['A','C','D','E','F','G','H','I','K','L','M','N','P','Q','R','S','T','V','W',',Y']
• Note: The refernce database table should be tab delimited.

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Contribution:

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AMPcombi is a tool developed for parsing results from published AMP prediction tools. We therfore welcome fellow contributers who would like to add new AMP prediction tools results for parsing and alignment.

Adding a new tool to AMPcombi

In ampcombi/reformat_tables.py

• add a new tool function to read the output to a pandas dataframe
• add the new function to the read_path function

In ampcombi/main.py

• add your default tool:tool.fileendingto the default of --tooldict

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Authors: @louperelo and @darcy220606