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Modeling Zero-Inflated Microbiome Data

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Book cover Statistical Analysis of Microbiome Data with R

Part of the book series: ICSA Book Series in Statistics ((ICSABSS))

Abstract

In this chapter, we introduce and illustrate how to model zero-inflated microbiome data. In Sect. 12.1, we briefly introduce modeling zero-inflated data. The remaining of this chapter is organized as follows: Sect. 12.2 introduce zero-inflated Poisson (ZIP) and negative binomial model (ZINB) and their implementations in real microbiome data. Section 12.3 introduce zero-hurdle Poisson (ZHP) and zero-hurdle negative binomial (ZHNB) and implement them with the same data set. The zero-inflated beta regression model with random-effects (ZIBR) is covered and illustrated in Sect. 12.4. We conclude this chapter by a summary and discussion in Sect. 12.5.

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Authors and Affiliations

  1. Department of Medicine, University of Illinois at Chicago, Chicago, IL, USA

    Yinglin Xia & Jun Sun

  2. School of Social Work, University of North Carolina, Chapel Hill, NC, USA

    Ding-Geng Chen

  3. Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA

    Ding-Geng Chen

  4. Department of Statistics, University of Pretoria, Pretoria, South Africa

    Ding-Geng Chen

Authors
  1. Yinglin Xia
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  2. Jun Sun
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  3. Ding-Geng Chen
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Correspondence to Yinglin Xia .

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Xia, Y., Sun, J., Chen, DG. (2018). Modeling Zero-Inflated Microbiome Data. In: Statistical Analysis of Microbiome Data with R. ICSA Book Series in Statistics. Springer, Singapore. https://doi.org/10.1007/978-981-13-1534-3_12

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