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Microbiome `omics approaches can reveal intriguing relationships between the human microbiome and certain disease states. Along with the identification of specific bacteria taxa associated with diseases, recent scientific advancements…

应用统计 · 统计学 2019-10-07 Shuang Jiang , Guanghua Xiao , Andrew Y. Koh , Qiwei Li , Xiaowei Zhan

Detecting associations between microbial compositions and sample characteristics is one of the most important tasks in microbiome studies. Most of the existing methods apply univariate models to single microbial species separately, with…

统计方法学 · 统计学 2021-03-18 Boyu Ren , Sergio Bacallado , Stefano Favaro , Tommi Vatanen , Curtis Huttenhower , Lorenzo Trippa

Microorganisms play critical roles in human health and disease. It is well known that microbes live in diverse communities in which they interact synergistically or antagonistically. Thus for estimating microbial associations with clinical…

One of the major research questions regarding human microbiome studies is the feasibility of designing interventions that modulate the composition of the microbiome to promote health and cure disease. This requires extensive understanding…

统计方法学 · 统计学 2021-11-18 Matthew D. Koslovsky , Kristi L. Hoffman , Carrie R. Daniel , Marina Vannucci

Dimension reduction of high-dimensional microbiome data facilitates subsequent analysis such as regression and clustering. Most existing reduction methods cannot fully accommodate the special features of the data such as count-valued and…

统计方法学 · 统计学 2023-05-02 Tianchen Xu , Ryan T. Demmer , Gen Li

The advances of next-generation sequencing technology have accelerated study of the microbiome and stimulated the high throughput profiling of metagenomes. The large volume of sequenced data has encouraged the rise of various studies for…

统计方法学 · 统计学 2019-04-30 Qiwei Li , Shuang Jiang , Andrew Y. Koh , Guanghua Xiao , Xiaowei Zhan

Scientific studies in the last two decades have established the central role of the microbiome in disease and health. Differential abundance analysis seeks to identify microbial taxa associated with sample groups defined by a factor such as…

统计方法学 · 统计学 2023-12-29 Archie Sachdeva , Somnath Datta , Subharup Guha

Understanding the association between dietary patterns and health outcomes, such as the cancer risk, is crucial to inform public health guidelines and shaping future dietary interventions. However, dietary intake data present several…

统计方法学 · 统计学 2025-10-10 Blake Hansen , Dafne Zorzetto , Valeria Edefonti , Roberta De Vito

Microorganisms play a critical role in host health. The advancement of high-throughput sequencing technology provides opportunities for a deeper understanding of microbial interactions. However, due to the limitations of 16S ribosomal RNA…

统计方法学 · 统计学 2021-05-12 Hee Cheol Chung , Irina Gaynanova , Yang Ni

Microbiome research has immense potential for unlocking insights into human health and disease. A common goal in human microbiome research is identifying subgroups of individuals with similar microbial composition that may be linked to…

统计方法学 · 统计学 2025-08-21 Suppapat Korsurat , Matthew D. Koslovsky

Many data sets cannot be accurately described by standard probability distributions due to the excess number of zero values present. For example, zero-inflation is prevalent in microbiome data and single-cell RNA sequencing data, which…

统计方法学 · 统计学 2024-11-20 Max Beveridge , Zach Goldstein , Hee Cheol Chung

High-throughput sequencing technology provides unprecedented opportunities to quantitatively explore human gut microbiome and its relation to diseases. Microbiome data are compositional, sparse, noisy, and heterogeneous, which pose serious…

统计方法学 · 统计学 2020-10-12 Fangting Zhou , Kejun He , Qiwei Li , Robert S. Chapkin , Yang Ni

Numerous studies have shown that microbial metabolites, which represent the products of bacteria in the human gut, play a key role in shaping cancer risk and response to treatment. However, metabolite data typically contain a large…

应用统计 · 统计学 2026-05-19 Kai Jiang , Satabdi Saha , Christine B. Peterson

The role of the microbiome in disease pathogenesis is an emerging field with strong evidence suggesting that dysbiosis is associated with precancerous and cancerous states. Microbiome data present substantial challenges for causal mediation…

统计方法学 · 统计学 2026-05-07 Seungjun Ahn , Quran Wu , Alicia Yang , Zhigang Li

Human microbiome studies based on genetic sequencing techniques produce compositional longitudinal data of the relative abundances of microbial taxa over time, allowing to understand, through mixed-effects modeling, how microbial…

统计方法学 · 统计学 2025-12-23 John Barrera , Cristian Meza , Ana Arribas-Gil

The infant microbiome undergoes rapid changes in composition over time and is associated with long-term risks of conditions such as immune strength, allergy, asthma, and other health outcomes. Modeling the associations between exposures or…

统计方法学 · 统计学 2026-03-31 Brody Erlandson , Ander Wilson , Matthew D. Koslovsky

The human microbiome can contribute to pathogeneses of many complex diseases by mediating disease-leading causal pathways. However, standard mediation analysis methods are not adequate to analyze the microbiome as a mediator due to the…

Recent advances in bioinformatics have made high-throughput microbiome data widely available, and new statistical tools are required to maximize the information gained from these data. For example, analysis of high-dimensional microbiome…

统计方法学 · 统计学 2017-03-23 Neal S. Grantham , Brian J. Reich , Elizabeth T. Borer , Kevin Gross

The human microbiome plays critical roles in human health and has been linked to many diseases. While advanced sequencing technologies can characterize the composition of the microbiome in unprecedented detail, it remains challenging to…

We consider the complex data modeling problem motivated by the zero-inflated and overdispersed data from microbiome studies. Analyzing how microbiome abundance is associated with human biological features, such as BMI, is of great…

统计方法学 · 统计学 2025-03-31 Zirui Wang , Tianying Wang
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