# Advanced Statistical Methods for Microbiome Data Analysis

> **NIH NIH R01** · UNIVERSITY OF WISCONSIN-MADISON · 2021 · $256,235

## Abstract

Thanks to advances in high-throughput sequencing technologies, the importance of the microbiome in
human health and disease has been increasingly recognized. The development of robust and powerful
methods that adapt to the features of the microbiome data has seriously fallen behind the technological
advances, especially for the application to the study of complex diseases. Motivated by ongoing
microbiome projects, we propose to develop a meta-analysis method to synthesize multiple microbiome
association studies; a method to analyze longitudinal microbiome data; and a method to identify microbial
co-variation clusters. We will develop software programs implementing these methods and apply them in
ongoing microbiome studies. The methods and tools resulting from this project will promote a better
understanding of the role of the microbiome for human health and disease.
RELEVANCE (See instructions):
Microbiome research is a promising area to understand mechanisms underpinning complex human
diseases. The unique structure and characteristics of microbiome data render many standard analytic
approaches inadequate. In this application, we propose to develop advanced methods and computational
tools for microbiome data analyses and apply the methods to ongoing projects to uncover the roles of
microbiome for complex human diseases.

## Key facts

- **NIH application ID:** 10242959
- **Project number:** 5R01GM140464-02
- **Recipient organization:** UNIVERSITY OF WISCONSIN-MADISON
- **Principal Investigator:** Zhengzheng Tang
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $256,235
- **Award type:** 5
- **Project period:** 2020-09-01 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10242959

## Citation

> US National Institutes of Health, RePORTER application 10242959, Advanced Statistical Methods for Microbiome Data Analysis (5R01GM140464-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10242959. Licensed CC0.

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