AMPcombi 0.1.3

A parsing tool for AMP tools.

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:

Tool	Version	Link
Ampir	1.1.0	https://github.com/Legana/ampir
AMPlify	1.0.3	https://github.com/bcgsc/AMPlify
Macrel	1.1.0	https://github.com/BigDataBiology/macrel
HMMsearch	3.3.2	https://github.com/EddyRivasLab/hmmer
EnsembleAMPpred	-	https://pubmed.ncbi.nlm.nih.gov/33494403/
NeuBI	-	https://github.com/nafizh/NeuBI

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

Tool	Version	Link
DRAMP	3.0	https://github.com/CPU-DRAMP/DRAMP-3.0

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/ --faa_folder path/to/sample_faa_files/

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.

The path to the folder containing the respective protein fasta files has to be provided with --faa_folder. The files have to be named with <samplename>.faa.

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] --faa_folder path/to/sample_faa_files/

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. The path to the folder containing the respective protein fasta files has to be provided with --faa_folder. The files have to be named with <samplename>.faa.

Input options:

command	definition	default	example
--amp_results	path to the folder containing different tool's output files	./test_files/	../amp_results/
--sample_list	list of samples' names	[]	[sample_1, sample_2]
--path_list	list of paths to output files	[]	[[paths to sample_1 output], [paths to sample_2 outputs]]
--outdir	name of the output directory	./ampcombi_results/	./ampcombi_results/
--cutoff	probability cutoff to filter AMPs	0	0.5
--faa_folder	path to the folder containing the samples` .faa files, Filenames have to contain the corresponding sample-name, i.e. sample_1.faa	./test_faa/	./faa_files/
--tooldict	dictionary of AMP-tools and their respective output file endings	{'ampir':'ampir.tsv', 'amplify':'amplify.tsv', 'macrel':'macrel.tsv', 'hmmer_hmmsearch':'hmmsearch.txt', 'ensembleamppred':'ensembleamppred.txt'}	-
--amp_database	path to the folder containing the reference database files: (1) a fasta file with <.fasta> file extension and (2) the corresponding table with with functional and taxonomic classifications in <.tsv> file extension	DRAMP 'general amps' database	./amp_ref_database/

• 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