AGAMEMNON: an Accurate metaGenomics And MEtatranscriptoMics quaNtificatiON analysis suite.

Area of Science:

• Microbiology
• Bioinformatics
• Genomics

Background:

• Accurate microbial abundance quantification is crucial for understanding complex biological systems.
• Existing methods may face challenges with large datasets or specific sample types like host-associated microbes.

Purpose of the Study:

• To introduce AGAMEMNON, a novel computational tool for precise microbial abundance profiling.
• To enable efficient analysis of diverse sequencing data, including metagenomics, metatranscriptomics, and host-associated samples.

Main Methods:

• Development of AGAMEMNON, featuring a time and space-efficient indexing scheme for rapid pattern matching.
• Integration of host-specific modules for accurate microbial quantification from host tissue RNA/DNA sequencing.
• Implementation of an R-Shiny application for user-friendly investigation and data visualization.

Main Results:

• AGAMEMNON achieves accurate microbial abundance quantification at genus, species, and strain resolution.
• The tool efficiently indexes and analyzes vast datasets using standard computational resources.
• Host-specific modules demonstrate exceptional accuracy for microbial abundance estimation in host samples.

Conclusions:

• AGAMEMNON provides a powerful and accessible solution for microbial abundance analysis across multiple sequencing types.
• The tool's efficiency and accuracy, particularly with host-associated samples, expand research capabilities.
• The integrated R-Shiny interface facilitates data exploration and interpretation for a wider user base.