The article introduces QIIME (Quantitative Insights into Microbial Ecology), an open-source software pipeline designed to handle high-throughput community sequencing data. QIIME addresses the challenge of analyzing massive datasets from microbial ecology studies, which have become increasingly common due to advancements in sequencing technologies like Pyrosequencing. The software supports a wide range of microbial community analyses, including network analysis, diversity histograms, and the identification of 'core' microbial sets in specific habitats. QIIME is highly modular, allowing for easy integration and benchmarking of various functionalities such as OTU selection, sequence alignment, and phylogenetic tree inference. The authors demonstrate the effectiveness of QIIME by applying it to a combined analysis of gut bacterial communities from mice, human twins, and germ-free mice colonized with human fecal microbiota. This analysis involved 3.8 million bacterial 16S rRNA sequences from multiple studies. QIIME is expected to continue evolving to keep pace with advancements in sequencing technology and to facilitate the characterization of microbial community patterns in various ecosystems.The article introduces QIIME (Quantitative Insights into Microbial Ecology), an open-source software pipeline designed to handle high-throughput community sequencing data. QIIME addresses the challenge of analyzing massive datasets from microbial ecology studies, which have become increasingly common due to advancements in sequencing technologies like Pyrosequencing. The software supports a wide range of microbial community analyses, including network analysis, diversity histograms, and the identification of 'core' microbial sets in specific habitats. QIIME is highly modular, allowing for easy integration and benchmarking of various functionalities such as OTU selection, sequence alignment, and phylogenetic tree inference. The authors demonstrate the effectiveness of QIIME by applying it to a combined analysis of gut bacterial communities from mice, human twins, and germ-free mice colonized with human fecal microbiota. This analysis involved 3.8 million bacterial 16S rRNA sequences from multiple studies. QIIME is expected to continue evolving to keep pace with advancements in sequencing technology and to facilitate the characterization of microbial community patterns in various ecosystems.