Chapter title |
Processing and Analyzing Human Microbiome Data
|
---|---|
Chapter number | 31 |
Book title |
Statistical Human Genetics
|
Published in |
Methods in molecular biology, January 2017
|
DOI | 10.1007/978-1-4939-7274-6_31 |
Pubmed ID | |
Book ISBNs |
978-1-4939-7273-9, 978-1-4939-7274-6
|
Authors |
Xuan Zhu, Jian Wang, Cielito Reyes-Gibby, Sanjay Shete |
Abstract |
The human microbiome is associated with complex disorders such as diabetes, cancer, obesity and cardiovascular disorders. Recent technological developments have allowed researchers to fully quantify the composition of the microbiome using culture-independent approaches, resulting in a large amount of microbiome data, which provide invaluable opportunities to assess the important contributions of the microbiome to human health and disease. In this chapter, we discuss and evaluate multiple statistical approaches for processing, summarizing, and analyzing microbiome data. Specifically, we provide programming scripts for processing microbiome data using QIIME and calculating alpha and beta diversities, assessing the association between diversities and outcomes of interest using R programs, as well as interpretation of results. We illustrate the methods in the context of analyzing the foregut microbiome in esophageal adenocarcinoma. |
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Professor | 1 | 4% |
Other | 0 | 0% |
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Veterinary Science and Veterinary Medicine | 1 | 4% |
Other | 1 | 4% |
Unknown | 12 | 52% |