Microbiome for beginners

This section is currently under construction, and we hope to collect resources (recommended reading, helpful tutorials, etc.) that are useful to those just starting out in microbiome research. This is aimed at new members of the lab group, but we think it may be useful for others, too. If there are resources that you have found helpful and we haven't included here, we'd love to hear about them. It won't be necessary to work through everything that's here in order for you to be able to process your own data, but different parts of it will probably be useful at different stages.

If you are at Dalhousie, we would encourage you to join our Dalhousie Microbiome User Group (DalMUG) - we hold a journal club every two weeks where we discuss a new microbiome paper. You can find summaries of previous papers on the site, and also join the Google group where we send out details of the next meetings and sometimes other useful things like upcoming conferences. These are informal meetings where one person will usually lead the discussion on a paper, but anyone should feel welcome to jump in with questions or comments.

Descriptions of work flows

These are all YouTube videos giving an overview of some aspect of microbiome sequencing or data analysis.

Amplicon sequencing - 16S rRNA gene sequencing, Illumina YouTube webinar, What is 16S sequencing?
Amplicon sequencing taxonomic analysis - Bioinformatic analysis of 16S rRNA sequencing data
Amplicon sequencing functional prediction
Shotgun metagenomic sequencing - Introduction to metagenomics
Taxonomic analysis of shotgun metagenomic sequencing - IMPACTT 2022
Functional analysis of shotgun metagenomic sequencing - IMPACTT 2022
Construction of Metagenome Assembled Genomes (MAGs) from shotgun metagenomic sequencing data - Metagenome Analysis, Binning and Extracting Genomes
Other - 16S sequencing vs shotgun metagenomics, Canadian Bioinformatics Workshops (series of tutorials from different years that the workshops were run)
Introduction to Microbial 'Omics on the Meren Lab website (not a Youtube video)

Recommended reading

Here we have some papers that we think give a great overview of microbiome research and what a typical analysis workflow might look like as well as some papers that give a deeper dive on a particular topic. It is worth noting that as microbiome research is still a relatively new field (as we know it now, at least - leaning heavily on nucleic acid sequencing and bioinformatics for analysis). There are therefore several topics that are a bit contentious and many researchers disagree on the correct, or best, way to deal with them. In several cases, there are multiple methods/tools that are all designed for the same task. Researchers will also often have particular tools that they like using and may feel strongly about the use of different tools - or there may be tools that are possibly able to perform "better" than those, but if development isn't continued then these can often become very difficult to actually use (particularly for someone for which bioinformatics is only a small part of the methods that they use). My personal take on this is that the most important thing is that you should understand the methods you use, know why you are using those methods and also be aware of what the limitations of those methods are.

Compositional data analysis

Gregory B. Gloor, Jean M. Macklaim, Vera Pawlowsky-Glahn & Juan J. Egozcue (2017) Microbiome Datasets Are Compositional: And This Is Not Optional

Rarefying

Paul J. McMurdie & Susan P. Holmes (2014) Waste Not, Want Not: Why Rarefying Microbiome Data Is Inadmissible

Differential abundance analysis

Jacob T. Nearing, Gavin M. Douglas, Molly G. Hayes, et al. (2022) Microbiome differential abundance methods produce different results across 38 datasets
Sophie Weiss, Zhenjiang Zech Xu, Shyamal Peddada, et al. (2017) Normalization and microbial differential abundance strategies depend upon data characteristics

Additional considerations for metagenomic analyses

Robyn J. Wright, André M. Comeau & Morgan G.I. Langille (preprint) From defaults to databases: parameter and database choice dramatically impact the performance of metagenomic taxonomic classification tools
Alexander Sczyrba, Peter Hofmann, Peter Belmann et al. (2017) Critical Assessment of Metagenome Interpretation—a benchmark of metagenomics software
Fernando Meyer, Adrian Fritz, Zhi-Luo Deng, et al. (2022) Critical Assessment of Metagenome Interpretation: the second round of challenges - you can read a summary of the discussion our DalMUG journal club had about the preprint of this paper here.

Slightly random resources, mainly taken from Twitter

Contact

Please feel free to post a question on the Microbiome Helper google group if you have any issues.
General comments or inquires about Microbiome Helper can be sent to morgan.langille@dal.ca.