MetaPont 0.0.2

MetaPont - A tool to bridge the gap between the output of metagenomic tools and the analysis of the data

MetaPont

MetaPont - A tool to bridge the gap between the output of metagenomic tools and the analysis of the data

Features - These are the current aims of this project - Still under development

• Targeted Functional Analysis: Search for specific functional IDs (e.g., GO terms) within the .tsv files provided by the HuwsLab Metagenome Workflow (https://github.com/TheHuwsLab/Metagenome_Workflow) .
• Taxonomic Breakdown: Extract genus-level taxonomy information and calculate their proportions in the dataset.
• Batch Processing: Analyse all .tsv files in a specified directory.
• Customisable Output: Save results in a format suitable for downstream analysis.

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Installation

Prerequisites

Ensure you have the following installed:

• Python ~3.6 or later
• Required Python libraries: argparse, csv, and collections (standard libs).

Installation via pip

MetaPont is provided as a pip distribution.

pip install MetaPont 

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Usage

Command-line Arguments

Extract-By-Function -h

usage: Extract-By-Function [-h] -d DIRECTORY -f FUNCTION_ID [-o OUTPUT] [-m MIN_PROPORTION]

MetaPont v0.0.2: Extract-By-Function - Identify taxa contributing to a specific function.

options:
  -h, --help            show this help message and exit
  -d DIRECTORY, --directory DIRECTORY
                        Directory containing TSV files to analyse.
  -f FUNCTION_ID, --function_id FUNCTION_ID
                        Specific function ID to search for (e.g., 'GO:0002').
  -o OUTPUT, --output OUTPUT
                        Output file to save results (default: output_taxa_details.tsv).
  -m MIN_PROPORTION, --min_proportion MIN_PROPORTION
                        Minimum proportion threshold for taxa to be included in the output (default: 0.05).

The Extract-By-Function tool provides several command-line options:

Option	Description	Required	Default
-d, --directory	Directory containing .tsv files to analyse.	Yes	None
-f, --function_id	Functional ID to search for (e.g., GO:0002).	Yes	None
-m, --min_proportion	Minimum proportion needed for reporting.	Yes	0.05 (5%)
-o, --output	Output file name to save results.	No	output_taxa_proportions.tsv

Example

To search for the functional ID GO:0002 in all .tsv files within the data/ directory:

ExtractByFunction -d .../test_data/Final_contig/ -f GO:0002 -m 0.10 -o .../test_data/Final_Contig/Extract_By_Function_Out/results.tsv

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Output

The tool generates a tab-delimited output file with the following columns:

1. Sample: Name of the processed .tsv file.
2. Taxa: Genus-level taxonomic assignment extracted from the Lineage column.
3. Proportion: Proportion of matches to the given functional ID within the sample.

Example output:

Function ID: GO:0002
Sample	Taxa	Reads Assigned (Function)	Proportion (Function)	Proportion (Total Reads)
PN0536_0003_S83_Final_Contig.tsv	Gordonibacter	60788	0.075	0.002
PN0536_0003_S83_Final_Contig.tsv	Streptomyces	115671	0.142	0.004
PN0536_0003_S83_Final_Contig.tsv	unknown	80890	0.099	0.003
PN0536_0003_S83_Final_Contig.tsv	Clostridium	51018	0.063	0.002
PN0536_0003_S83_Final_Contig.tsv	Lactobacillus	149909	0.184	0.005
PN0536_0003_S83_Final_Contig.tsv	Limosilactobacillus	79694	0.098	0.003

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Implementation Details

Workflow

1. The script reads .tsv files from the specified directory.
2. For each file, it searches for occurrences of the given functional ID within specific columns.
3. Matches are associated with genus-level taxonomic information extracted from the Lineage column.
4. Taxa proportions are calculated and saved to the output file.

Large File Handling (Might be a failure point)

The script uses csv.field_size_limit to handle exceptionally large .tsv files.

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Future Plans

• Add support for additional file formats (e.g., .csv, .txt).
• Expand functionality for more complex taxonomic and functional analyses.

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