Fall 2020: Investigating Microbial Communities

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Introduction to QIIME environment and DADA2.

BIT 477/577 Fall 2020 Students

Module Learning Objectives (MOs)

  • MO 5.1. Compare and contrast OTUs and ASVs.
  • MO 5.2. Discuss and critically evaluate each step of a 16S QIIME standard operating procedure (SOP).
  • MO 5.3. Perform basic data analyses using QIIME and a downloaded dataset.
  • MO 5.4. Apply tools from QIIME tutorial to analyses of other data sets:
    1. Create OTU tables to use for analyses in QIIME and elsewhere (e.g., R for plotting)
    2. Use alpha and beta diversity tools to assess richness and diversity within and between samples.
    3. Plot several different types of graphs using QIIME’s interface.
  • MO. 5.5. Define and explain the concepts of metadata, OTU, rarefaction curve.

Rarefaction

A definition of rarefaction curves and why we use them: https://blogs.iu.edu/ncgas/2019/09/04/rarefaction-curves-for-metagenomic-datasets/

Rarefying data can be “controversial.” It is worth learning these arguments if you choose to rarefy (as is done in the paper for this week’s reading) in case you are met with questions and criticisms down the line.

Here is an argument against it: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003531

Here is a paper that weighs the pros and cons: https://www.biorxiv.org/content/10.1101/2020.09.09.290049v1.full

Another resource for QIIME!

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3249058/

 

OTUs, ASVs, and DADA2:

Here’s an article further explaining the benefits of using ASV’s: https://www.nature.com/articles/ismej2017119

Another resource from Zymo, especially nice if you prefer text over video: https://www.zymoresearch.com/blogs/blog/microbiome-informatics-otu-vs-asv

https://www.bioconductor.org/help/course-materials/2016/BioC2016/InvitedTalks1/160624-Holmes-MultitableMicrobiomeBioc.pdf

This paper discusses the use of ASVs and OTUs on the same experimental data sets and concludes that there is no significant difference. It’s kind of a counter-argument to Ben Callahan’s paper mentioned above, and serves to validate studies that have used OTUs in the past.

https://msphere.asm.org/content/3/4/e00148-18

 

QIIME and the HPC

Since we are discussing HPC and Henry2, it may be useful to link the Henry2 guides on NCSU’s website. They already have easy to use scripts for many languages (R, Python, Matlab) if anyone needs the extra computing resources. They are also very good at working with researchers if you have a particular request.

https://projects.ncsu.edu/hpc/Documents/GetStarted.php

 

Here is a link to a 16S rRNA SOP that can be applied to QIIME:

https://h3abionet.org/images/SOPs/16S_rRNA_diversity_analysis_SOP.pdf

This site along with the tutorials posted on Moodle helped me understand how to input commands for the tutorial.  I am still pretty new to coding and using a command-line interface, so finding information that is easy to digest is very helpful: https://maker.pro/linux/tutorial/basic-linux-commands-for-beginners

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