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Microbiome Data Analysis Using QIIME2 (MBQM01)
24 June 2019 - 28 June 2019
This course will provide a theoretical, analytical and practical introduction to QIIME 2 (canonically pronounced ‘chime two’), which stands for Quantitative Insights into Microbial Ecology 2, and Qiita (canonically pronounced ‘cheetah’), a multiomics and multi-study online tool. QIIME 2 and Qiita are open source software packages for comparison and analysis of microbial communities, primarily based on high-throughput amplicon sequencing data (such as SSU rRNA) generated on a variety of platforms, but also supporting analysis of other types of data (such as shotgun metagenomic, metabolomics or proteomics). The main Qiita deployment (http://qiita.microbio.me/) allows users to manage and analyze large studies, their metadata and the multiple data types generated from the same samples. Additionally, it allows users to combine their samples with other published and public studies available in the system. QIIME 2 is a stand-alone environment for the analysis of individual microbiome data sets that can be used on your laptop, university computational resources, and cloud computing resources.
By the end of the course, participants will be able to:
- Understand the most recent QIIME2 and Qiita features for microbial community analysis
- Select the best workflow and parameters to perform the different steps for microbial community analysis
- Understand and apply on their own datasets different phylogenetic and non-phylogenetic metrics to compare microbial diversity samples
- Upload and analyze their own datasets using Qiita and compare their studies with other public studies
To find out more or to book online via our sister company (PR informatics) use the link below…
The instructors were excellent and clearly were the reasons for my previous comments. They both combined a deep understanding of statistics and ecology at the same level.Any questions or queries I’ve had, were thus first answered with an ecological point of view and then translated into statistical consideration thereby making much more sense on both side.In addition the course was very well organised, the course director and the two instructors were very friendly as well as professional. On the top of learning many useful things, I’ve also had a very good time during the week there.” Clement Garcia,
Spatial ecologist, Centre For Environment, Fisheries & Aquaculture Science (CEFAS), England
(Attended ADVR course)