mbImpute: an accurate and robust imputation method for microbiome data [article]

Ruochen Jiang, Wei Vivian Li, Jingyi Jessica Li
2020 bioRxiv   pre-print
Microbiome studies have gained increased attention since many discoveries revealed connections between human microbiome compositions and diseases. A critical challenge in microbiome research is that excess false zeros distort taxon abundances, complicate data analysis, and jeopardize the reliability of scientific discoveries. To address this issue, we propose the first imputation method, mbImpute, to identify and recover likely false zeros by borrowing information jointly from similar samples,
more » ... imilar taxa, and optional metadata including sample covariates and taxon phylogeny. Comprehensive simulations verified that mbImpute achieved better imputation accuracy under multiple measures than five state-of-the-art imputation methods designed for non-microbiome data. In real data applications, we demonstrate that mbImpute improved the power and reproducibility of identifying disease-related taxa from microbiome data of type 2 diabetes and colorectal cancer.
doi:10.1101/2020.03.07.982314 fatcat:tdps3yabhrhv3lyo7gpswq2x3a