Metaxa

Metaxa identifies and classifies small-subunit (SSU) ribosomal RNA sequences (12S/16S/18S) in complex sequence datasets to assign taxonomic origin among bacteria, archaea, nuclear eukaryotes, chloroplasts, and mitochondria.

Key Features:

• Automated identification and extraction: Automates identification and extraction of SSU rRNA sequences from large or complex sequence datasets.
• Comprehensive origin classification: Classifies SSU rRNA sequences into archaeal, bacterial, nuclear eukaryote, mitochondrial, or chloroplast origin.
• HMM-based detection and scoring: Uses Hidden Markov Models (HMMs) to detect and score SSU rRNA sequences and infer origin with high precision.
• Integration of reference data: Leverages reference databases and full-length organelle and organism genomes to improve classification accuracy.
• Robust on partial and full-length sequences: Handles and classifies both partial and full-length SSU rRNA sequences from metagenomic datasets.

Scientific Applications:

• Microbial ecology: Assigns SSU rRNA sequences to origins to characterize microbial community composition and diversity in environmental samples.
• Evolutionary biology: Provides origin assignments of SSU rRNA sequences to support studies of evolutionary relationships among organisms.
• Metagenomics: Extracts and classifies SSU rRNA sequences from metagenomic datasets to profile taxonomic composition of complex samples.

Methodology:

Metaxa employs Hidden Markov Models (HMMs) to detect and score SSU rRNA sequences and leverages reference databases plus full-length organelle and organism genomes to inform classification of partial and full-length sequences.