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Assessment and Selection of Competing Models for Zero-Inflated Microbiome Data
2015
PLoS ONE
Typical data in a microbiome study consist of the operational taxonomic unit (OTU) counts that have the characteristic of excess zeros, which are often ignored by investigators. In this paper, we compare the performance of different competing methods to model data with zero inflated features through extensive simulations and application to a microbiome study. These methods include standard parametric and non-parametric models, hurdle models, and zero inflated models. We examine varying degrees
doi:10.1371/journal.pone.0129606
pmid:26148172
pmcid:PMC4493133
fatcat:ttwtr6whu5caflkc3kh4m6rynm