OverviewTeaching: 5 min
Exercises: 10 minQuestions
Where are other metagenomic resources?Objectives
Know some places where to find more information.
Other tutorials and books
Now that you finished this metagenomic lesson, you are ready
to explore on your own the universe of available tutorials.
Phyloseq tutorial contains much more examples of metagenomic data manipulation.
The Computational Genomics tutorial by Schmeier explains each step of the process carefully. There is a beautiful entry called [History of metagenomics] in the Meren Lab blog (http://merenlab.org/2020/07/27/history-of-metagenomics/) as well as several videos explaining Metapangenomics: A nexus between pangenomes and metagenomes, The power of metagenomic read recruitment, Genome-resolved metagenomics: key concepts in reconstructing genomes from metagenomes. Finally, for Spanish speakers, the ISME course is a detailed tutorial for 16s metabarcoding ISME Análisis de diversidad.
The book Microbiomes shares a contemporary concept of microbiomes. Books Statistical analysis of microbiome data and statistical analysis of microbiome data with r contain a state-of-the-art compendium of the statistical and computational microbiome analysis techniques beyond diversity analysis.
Other studies and databases
A valuable and easy-to-use resource is MG-RAST, which is at the same time a database and an online analysis tool. MG-RAST is an online metagenomic platform where you can upload your raw data with its corresponding metadata and get a complete taxonomic analysis of it. MG-RAST is a great place to get started in this type of analysis, and it is also an extensive repository of available data for future experiments. On the downside, it is not possible to modify significantly the steps and parameters in the MG-RAST workflow, so there is little room when it comes to implementing our preferred analysis tools when using MG-RAST.
The Cuatro Ciénegas data that we used in the workshop is already in MG-RAST! You can check it out here.
We can check the taxonomical distribution of our sample at different taxonomical levels.
Since we have a shotgun metagenome, we can also investigate the metabolic functions present in our sample. MG-RAST can find genes and annotate their function through the implementation of RAST or Rapid Annotation using Subsystems Technology. By looking at the charts generated by this analysis, we see that most of the genes are dedicated to metabolism.
MG-RAST has its own specific pipeline, so it is a handy tool to have a quick look at your data and also to store and share it! However, it does not keep you from making your own personalized analysis like we just learned!
Discussion: Exploring more resources
Explore one of the suggested resources and discuss your findings with a neighbor.
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