An overview of modern applications of negative binomial modelling in ecology and biodiversity

J Stoklosa, RV Blakey, FKC Hui - Diversity, 2022 - mdpi.com
Negative binomial modelling is one of the most commonly used statistical tools for analysing
count data in ecology and biodiversity research. This is not surprising given the prevalence …

A review of normalization and differential abundance methods for microbiome counts data

D Swift, K Cresswell, R Johnson… - Wiley …, 2023 - Wiley Online Library
The recent development of cost‐effective high‐throughput DNA sequencing technologies
has tremendously increased microbiome research. However, it has been well documented …

Overview of data preprocessing for machine learning applications in human microbiome research

E Ibrahimi, MB Lopes, X Dhamo, A Simeon… - Frontiers in …, 2023 - frontiersin.org
Although metagenomic sequencing is now the preferred technique to study microbiome-host
interactions, analyzing and interpreting microbiome sequencing data presents challenges …

Challenges and opportunities in the statistical analysis of multiplex immunofluorescence data

CM Wilson, OE Ospina, MK Townsend, J Nguyen… - Cancers, 2021 - mdpi.com
Simple Summary Immune modulation is considered a hallmark of cancer initiation and
progression, and has offered promising opportunities for therapeutic manipulation. Multiplex …

Bayes factor of zero inflated models under jeffereys prior

P Pramanik, AK Maity - arxiv preprint arxiv:2401.03649, 2024 - arxiv.org
Microbiome omics data including 16S rRNA reveal intriguing dynamic associations between
the human microbiome and various disease states. Drastic changes in microbiota can be …

MB-GAN: microbiome simulation via generative adversarial network

R Rong, S Jiang, L Xu, G **ao, Y **e, DJ Liu, Q Li… - …, 2021 - academic.oup.com
Background Trillions of microbes inhabit the human body and have a profound effect on
human health. The recent development of metagenome-wide association studies and other …

A survey of statistical methods for microbiome data analysis

KC Lutz, S Jiang, ML Neugent, NJ De Nisco… - Frontiers in Applied …, 2022 - frontiersin.org
In the last decade, numerous statistical methods have been developed for analyzing
microbiome data generated from high-throughput next-generation sequencing technology …

A flexible zero-inflated poisson-gamma model with application to microbiome sequence count data

R Jiang, X Zhan, T Wang - Journal of the American Statistical …, 2023 - Taylor & Francis
In microbiome studies, it is of interest to use a sample from a population of microbes, such as
the gut microbiota community, to estimate the population proportion of these taxa. However …

A Bayesian zero-inflated Dirichlet-multinomial regression model for multivariate compositional count data

MD Koslovsky - Biometrics, 2023 - academic.oup.com
The Dirichlet-multinomial (DM) distribution plays a fundamental role in modern statistical
methodology development and application. Recently, the DM distribution and its variants …

Association of body index with fecal microbiome in children cohorts with ethnic–geographic factor interaction: accurately using a Bayesian zero-inflated negative …

J Huang, Y Lu, F Tian, Y Ni - Msystems, 2024 - journals.asm.org
The exponential growth of high-throughput sequencing (HTS) data on the microbial
communities presents researchers with an unparalleled opportunity to delve deeper into the …