Microbiome Analysis in R Using Microbiome | Bioinformatics Tutorial | Bioinformatics for Beginners
Title: Microbiome Analysis in R using microbiome Package | Alpha & Beta Diversity (Shannon, Observed, PCoA) | Wilcoxon Test
Description: Delve into microbiome analysis with R and the microbiome package in this detailed tutorial! We'll explore essential diversity metrics, including alpha diversity (using Shannon diversity and Observed species) and beta diversity (using PCoA). This tutorial will guide you through the analysis of gut microbiota data, showcasing how dietary changes impact microbial communities while utilizing the powerful microbiome package in R.
Key topics covered include:
Installing and using the microbiome package for microbiome analysis.
Understanding phyloseq objects (OTU tables, sample metadata, and taxonomy).
Analyzing real-world gut microbiota data related to colon cancer risk.
Calculating alpha diversity metrics like Shannon diversity (measuring species richness and evenness) and Observed species (total species count).
Performing a Wilcoxon test to assess statistical differences in alpha diversity between groups.
Investigating beta diversity using PCoA (Principal Coordinates Analysis) to visualize differences in microbial communities.
Creating PCoA plots and stacked barplots to visualize the microbial composition before and after a diet-swap.
Understanding the impact of diet changes on gut microbiota in African Americans and Native South Africans.
This tutorial is perfect for beginners and bioinformatics enthusiasts interested in learning microbiome analysis using R’s microbiome package. No prior experience required!
Don’t forget to subscribe for more tutorials on microbiome research, bioinformatics, and R programming.
Documentation:
https://rpubs.com/nabiilahardini/micr...
https://www.bioconductor.org/packages...
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