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Microbial community modelling and diversity estimation using the hierarchical Pitman-Yor process

Kevin McGregor, Aurélie Labbe, Celia MT Greenwood, Todd Parsons, Christopher Quince
doi: https://doi.org/10.1101/2020.10.24.353599
Kevin McGregor
1Department of Epidemiology, Biostatistics, and Occupational Health, McGill University
2Lady Davis Institute, Jewish General Hospital, Montréal, QC
3Warwick Medical School, University of Warwick, Coventry, United Kingdom
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Aurélie Labbe
4Département de sciences de la décision, HEC Montréal
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Celia MT Greenwood
1Department of Epidemiology, Biostatistics, and Occupational Health, McGill University
2Lady Davis Institute, Jewish General Hospital, Montréal, QC
5Gerald Bronfman Department of Oncology, McGill Department of Human Genetics, McGill University
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Todd Parsons
6Laboratoire de Probabilités, Statistique et Modélisation, Sorbonne Université, Paris, France
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Christopher Quince
3Warwick Medical School, University of Warwick, Coventry, United Kingdom
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  • For correspondence: c.quince@warwick.ac.uk
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Abstract

Background The human microbiome comprises the microorganisms that inhabit the various locales of the human body and plays a vital role in human health. The composition of a microbial population is often quantified through measures of species diversity, which summarize the number of species along with their relative abundances into a single value. In a microbiome sample there will certainly be species missing from the target population which will affect the diversity estimates.

Methods We employ a model based on the hierarchical Pitman-Yor (HPY) process to model the species abundance distributions over multiple microbiome populations. The model parameters are estimated using a Gibbs sampler. We also derive estimates of species diversity as a function of the HPY parameters.

Results We show that the Gibbs sampler for the HPY model performs well in the simulation study. We also show that the estimates of diversity from the HPY model improve over naïve estimates when species are missing. Similarly the HPY estimates tend to perform better than the naïve estimates when the number of individuals sampled from a population is small.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted October 25, 2020.
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Microbial community modelling and diversity estimation using the hierarchical Pitman-Yor process
Kevin McGregor, Aurélie Labbe, Celia MT Greenwood, Todd Parsons, Christopher Quince
bioRxiv 2020.10.24.353599; doi: https://doi.org/10.1101/2020.10.24.353599
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Microbial community modelling and diversity estimation using the hierarchical Pitman-Yor process
Kevin McGregor, Aurélie Labbe, Celia MT Greenwood, Todd Parsons, Christopher Quince
bioRxiv 2020.10.24.353599; doi: https://doi.org/10.1101/2020.10.24.353599

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