Large-Scale Meta-Longitudinal Microbiome Data with a Known Batch Factor

Vera-Khlara S. Oh, Robert W. Li
2022 Genes  
Data contamination in meta-approaches where multiple biological samples are combined considerably affects the results of subsequent downstream analyses, such as differential abundance tests comparing multiple groups at a fixed time point. Little has been thoroughly investigated regarding the impact of the lurking variable of various batch sources, such as different days or different laboratories, in more complicated time series experimental designs, for instance, repeatedly measured
more » ... data and metadata. We highlight that the influence of batch factors is significant on subsequent downstream analyses, including longitudinal differential abundance tests, by performing a case study of microbiome time course data with two treatment groups and a simulation study of mimic microbiome longitudinal counts.
doi:10.3390/genes13030392 pmid:35327945 pmcid:PMC8953633 fatcat:o4lypft57fgkffsj6qvv56vk6m