微生物群
数据科学
仿形(计算机编程)
可视化
人类微生物组计划
生物
计算机科学
统计推断
数据可视化
推论
基因组
人体微生物群
计算生物学
生物
数据挖掘
生物信息学
人工智能
自然(考古学)
统计
遗传学
古生物学
数学
基因
操作系统
作者
Christine B. Peterson,Satabdi Saha,Kim‐Anh Do
标识
DOI:10.1146/annurev-statistics-040522-120734
摘要
The microbiome represents a hidden world of tiny organisms populating not only our surroundings but also our own bodies. By enabling comprehensive profiling of these invisible creatures, modern genomic sequencing tools have given us an unprecedented ability to characterize these populations and uncover their outsize impact on our environment and health. Statistical analysis of microbiome data is critical to infer patterns from the observed abundances. The application and development of analytical methods in this area require careful consideration of the unique aspects of microbiome profiles. We begin this review with a brief overview of microbiome data collection and processing and describe the resulting data structure. We then provide an overview of statistical methods for key tasks in microbiome data analysis, including data visualization, comparison of microbial abundance across groups, regression modeling, and network inference. We conclude with a discussion and highlight interesting future directions.
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