EPheClass: ensemble-based phenotype classifier from 16S rRNA gene sequences.

ABSTRACT: One area of bioinformatics that is currently attracting particular interest is the classification of polymicrobial diseases using machine learning (ML), with data obtained from high-throughput amplicon sequencing of the 16S rRNA gene in human microbiome samples. The microbial dysbiosis underlying these types of diseases is particularly challenging to classify, as the data is highly dimensional, with potentially hundreds or even thousands of predictive features. In addition, the imbalance in the composition of the microbial community is highly heterogeneous across samples. In this paper, we propose a curated pipeline for binary phenotype classification based on a count table of 16S rRNA gene amplicons, which can be applied to any microbiome. To evaluate our proposal, raw 16S rRNA gene seque

SUBMITTER: Vazquez-Gonzalez L 

PROVIDER: S-EPMC12518240 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature