ICCTax: a hierarchical taxonomic classifier for metagenomic sequences on a large language model.

ABSTRACT:

Motivation

Metagenomic data increasingly reflect the coexistence of species from Archaea, Bacteria, Eukaryotes, and Viruses in complex environments. Taxonomic classification across the four superkingdoms is essential for understanding microbial communities, exploring genomic evolutionary relationships, and identifying novel species. This task is inherently imbalanced, uneven, and hierarchical. Genomic sequences provide crucial information for taxonomy classification, but many existing methods relying on sequence similarity to reference genomes often leave sequences misclassified due to incomplete or absent reference databases. Large language models offer a novel approach to extract intrinsic characteristics from sequences.

Results

We present ICCTax, a classifier integrating

SUBMITTER: Gao Y 

PROVIDER: S-EPMC12619997 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature