QIIME (pronounced "chime") stands for Quantitative Insights Into Microbial Ecologyrepairwear. QIIME is an open source software package for comparison and analysis of microbial communities, primarily bad on high-throughput amplicon quencing data
(such as SSU rRNA小亚基核糖体rna tactics/question/422472816.html四级计算器)
generated on a variety of platforms, but also supporting analysis of other types of data
abstraction
(新视野大学英语1读写教程答案such as shotgun metagenomic data metagenomic意思是宏基因组学，是对环境样品中微生物群体基因组进行的分析).
QIIME takes urs from their raw quencing output through initial analys such as OTU picking系统聚类, taxonomic assignment分类, and construction of phylogenetic trees系统树 from reprentative quences of OTUs, and through downstream statistical analysis, visualization, and production of publication-quality graphics. QIIME has been applied to适用于 single studies bad on warrantybillions of quences from thousands of samples.
This tutorial explains how to u the
studying abroad
QIIME (Quantitative Insights Into Microbial Ecology)
Pipeline to process data from high-throughput 16S rRNA quencing studies. If you have not already installed qiime, plea e the ction Installing Qiime first. The purpo of this
pipeline流水线
is to provide a cheekstart-to-finish workflow雅思词汇哪本书好, beginning with
multiplexed quence复合序列（多序列比对，整理分类和系统文件，比较样本，确定改变微生物群体形态的生物和环境因素）
reads and finishing with taxonomic and phylogenetic profiles and comparisons of the samples in the study. With this information in hand, it is possible to determine biological and environmental factors that alter microbial community ecology in your experiment.
As an example, we will u data from a study of the respon of mou gut microbial co
mmunities to fasting (Crawford et al., 2009). To make this tutorial run quickly on a personal computer, we will u a subt of the data generated from 5 animals kept on the control ad libitum fed diet, and 4 animals fasted for 24 hours before sacrifice. At the end of our tutorial, we will be able to compare the community structure of control vs. fasted animals. In particular, we will be able to compare taxonomic profiles for each sample type, differences in diversity metrics within the samples and between the groups, and perform comparative clustering analysis to look for overall differences in the samples.（给小鼠节食的例子）
In this walkthrough, text like the following:
print_qiime_config.py
denotes the command-line invocation命令行调用 of scripts. You can find full usage information for each script by passing the –h option (help) and/or by reading the full description in the Documentation. Execute all tutorial commands from within the qiime_tutorial directory, which can be downloaded from here: QIIME Tutorial files.
To process our data, we will perform the following analys, each of which is described in more detail below:
∙Filter the DNA quence reads for quality and assign multiplexed reads to starting samples by nucleotide barcode条码feed是什么意思翻译 .
∙Pick Operational Taxonomic Units (OTUs操作分类单元) bad on quence similarity within the reads, and pick a reprentative quence from each OTU.
∙Assign the OTU to a taxonomic identity using reference databas.
