So you want to be a MicrobiomeAnalyst?

Analysis of microbiota composition has been an ongoing pursuit for decades. However, the improved feasibility of next-generation sequencing techniques have greatly increased access to gigabytes of microbiome data. Whether you look at the hypervariable regions of bacterial 16S rRNA gene or metagenomic samples, the amount of data that can be overwhelming. Furthermore, researchers not trained in bioinformatic analysis, including biologists, immunologists, geologists and ecologists are struggling to analyze their own data. While several different platforms have been developed to improve microbiome analysis (ie. QIIME, mothur), these tools still require bioinformatic training.

Researchers from McGill University have attempted to bridge that gap by releasing MicrobiomeAnalyst, a free, web-based tool for in-depth microbiome analysis. This website allows for uploading your own files and give results including bacterial composition, community dynamics, and some statistical comparisons.  This will surely pique the interest of non-bioinformaticians to enhance their microbiome analysis throughput, while also potentially allowing standardization of analysis.  Nonetheless, it is important to assess this tool for its value to the community, especially whether bioinformaticians should: 1) fully endorse this as a tool, 2) “proceed at your own risk”, or 3) “You should not use this because…”.

The purpose of this journal club will be to assess this tool from several different angles:

  1. Who should be using this?
  2. What are the necessary data inputs for this tool?
  3. When should this be used? Hypothesis generation? Publication quality figures?
  4. How easy is this to use?
  5. Are the tools incorporated into the best tools to use?

Please join us Friday, May 26 3-4pm in HSC3N10A for the discussion of this tool.

Dhariwal, A., Chong, J., Habib, S., King, I., Agellon, LB., and Xia. J. (2017) “MicrobiomeAnalyst – a web-based tool for comprehensive statistical, visual and meta-analysis of microbiome data”
Nucliec Acids Research


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