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Day2-AmpliconR

Amplicon analysis in R

Resources

Suggested Reading

Weinroth MD, Belk AD, Dean C, et al. Considerations and best practices in animal science 16S ribosomal RNA gene sequencing microbiome studies. J Anim Sci. 2022;100(2):skab346. doi:10.1093/jas/skab346 Link

Ginnan N, Bordenstein SR. It is time to authenticate the Microbiome Sciences with accredited educational programs and departments. PLoS Biol. 2023 Dec 7;21(12):e3002420. doi: 10.1371/journal.pbio.3002420. PMID: 38060452; PMCID: PMC10703218. Link

Mirzayi C, Renson A; Genomic Standards Consortium; Reporting guidelines for human microbiome research: the STORMS checklist Nat Med. 2021 Nov;27(11):1885-1892. doi: 10.1038/s41591-021-01552-x. Epub 2021 Nov 17. PMID: 34789871; PMCID: PMC9105086.Link

Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJ, Holmes SP. DADA2: High-resolution sample inference from Illumina amplicon data. Nat Methods. 2016;13(7):581-583. doi:10.1038/nmeth.3869 Link

Gloor GB, Macklaim JM, Pawlowsky-Glahn V, Egozcue JJ. Microbiome Datasets Are Compositional: And This Is Not Optional. Front Microbiol. 2017;8:2224. Published 2017 Nov 15. doi:10.3389/fmicb.2017.02224 Link

Required Software

Software: R and Rstudio

Packages: dada2 , phyloseq, and tidyverse

Short lectures

Link to an overview of sequencing methodologies

Link to an overview of bioinformatics

Suggested Resources

Background: Coursera - gut check

It is great to start grappling with concepts - videos are short
https://www.coursera.org/lecture/microbiome/welcome-to-the-course-AuMZk

Coding:

🧑‍💻 The best way to get started with bioinformatics

For getting used to best practices in coding in the command line
https://www.biostarhandbook.com/index.html

🖥️ Getting started with R

  1. https://www.codecademy.com/learn/learn-r
  2. https://www.codecademy.com/search?query=R

💻 Getting started with BASH

Before you do biostars handbook do this quick shell one https://swcarpentry.github.io/shell-novice/

✅ Scientific rigor, reproducibility, version control, and code-alongs

Riffomonas has great tutorials to get started with R and reproducible research with version control is also a must. https://riffomonas.org/

🧬 16S analysis

16S analysis in R
https://benjjneb.github.io/dada2/tutorial.html

16S analysis in Qiime2
https://docs.qiime2.org/2021.11/tutorials/overview/