Processing-bias correction with DEBIAS-M improves cross-study generalization of microbiome-based prediction models.

ABSTRACT: Every step in common microbiome profiling protocols has variable efficiency for each microbe, for example, different DNA extraction efficiency for Gram-positive bacteria. These processing biases impede the identification of signals that are biologically interpretable and generalizable across studies. 'Batch-correction' methods have been used to address these issues computationally with some success, but they are largely non-interpretable and often require the use of an outcome variable in a manner that risks overfitting. We present DEBIAS-M (domain adaptation with phenotype estimation and batch integration across studies of the microbiome), an interpretable framework for inference and correction of processing bias, which facilitates domain adaptation in microbiome studies. DEBIAS-M learns

SUBMITTER: Austin GI 

PROVIDER: S-EPMC12087262 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature