TAMPA: TAxonoMic Profiling Analysis

This repository contains the official python implementation of the following paper: Sarwal, Varuni, Jaqueline Brito, Serghei Mangul, and David J. Koslicki. "TAMPA: interpretable analysis and visualization of metagenomics-based taxon abundance profiles." bioRxiv (2022).
(https://www.biorxiv.org/content/10.1101/2022.04.28.489926v1.abstract)

Setup Environment and Install Dependencies

Clone the repository

git clone git@github.com:dkoslicki/TAMPA.git
cd TAMPA

Installation with Conda

Please follow the instructions at the following link to set up anaconda: Anaconda Setup

The following commands create a conda environment inside the repository with the dependencies.

conda config --add channels defaults
conda config --add channels bioconda
conda config --add channels conda-forge
conda create -c etetoolkit -y -n CAMIViz python=3.7 numpy  ete3  seaborn pandas matplotlib biom-format
conda activate CAMIViz

Installation with Bioconda

Waiting for pull request to get merged

Example usage

python src/tampa.py -i data/prediction_multi.profile -g data/ground_truth_multi.profile phylum -s CAMI_HIGH_S001 -b basename -k linear -c False -r 1600 -o .

This should result in a plot that looks like:

TAMPA provides a "CONTRAST MODE" to better visualize the differences between the tool and gold standard. The contrast mode can be activated by setting the parameter c to True as follows

python src/tampa.py -i data/prediction_multi.profile -g data/ground_truth_multi.profile phylum -s CAMI_HIGH_S001 -b basename -k linear -c False -r 1600 -o .

This should result in a plot that looks like:

A comprehensive list of visualization options can be obtained using

python src/tampa.py --help

AlessioMilanese / TAMPA