TEMPTED: time-informed dimensionality reduction for longitudinal microbiome studies.

Longitudinal studies are crucial for understanding complex microbiome dynamics and their link to health. We introduce TEMPoral TEnsor Decomposition (TEMPTED), a time-informed dimensionality reduction method for high-dimensional longitudinal data that treats time as a continuous variable, effectively characterizing temporal information and handling varying temporal sampling. TEMPTED captures key microbial dynamics, facilitates beta-diversity analysis, and enhances reproducibility by transferring learned representations to new data. In simulations, it achieves 90% accuracy in phenotype classification, significantly outperforming existing methods. In real data, TEMPTED identifies vaginal microbial markers linked to term and preterm births, demonstrating robust performance across datasets and sequencing platforms.

Duke Scholars

Author Kouros Owzar Biostatistics & Bioinformatics, Division of Integrative Geno ...

Author Pixu Shi Biostatistics & Bioinformatics, Division of Integrative Geno ...

Author Anru Zhang Biostatistics & Bioinformatics, Division of Translational Bi ...