Kaiju

Kaiju performs taxonomic classification of high-throughput sequencing reads from technologies such as Illumina and Roche/454 by identifying maximum exact and inexact matches at the protein level against reference protein databases to assign taxonomy in metagenomic samples.

Key Features:

• Protein-Level Classification: Finds maximum exact and inexact matches at the protein level and leverages the Burrows-Wheeler transform for matching.
• Enhanced Sensitivity and Precision: Demonstrates higher sensitivity with comparable precision in genome exclusion benchmarks, improving classification for genera underrepresented in reference databases.
• Efficiency and Scalability: Processes millions of reads per minute, supporting large-scale metagenomic datasets.
• Broad Taxonomic Coverage: Uses the NCBI taxonomy and a reference database of protein sequences from Bacteria, Archaea, Fungi, microbial eukaryotes, and viruses.

Scientific Applications:

• Metagenomic community profiling: Assigns taxonomy in complex environmental or host-associated metagenomes to reveal community composition.
• Microbial ecology: Enhances detection of taxa in ecological studies, particularly for genera sparsely represented in databases.
• Human health and disease diagnostics: Enables deeper characterization of microbial communities in clinical and health-related samples, classifying up to ten times more reads than some traditional methods.

Methodology:

Direct taxonomic assignment by identifying maximum exact and inexact matches at the protein level using the Burrows-Wheeler transform against a protein reference database to overcome evolutionary divergence.