By Angus Ball

Introduction

One of the first steps you can do to analyze your data is make some relative abundance graphs. I'll show you how to make bar graphs. The data I use to do this example is from the FUNGuild importing Data page. Good Luck!

Theory

Relative abundance graphs are great! But relative abundance graphs can be created in a variety of ways using different transformations and whatnot. We will use a rather standard relative abundance: species reads/total reads in sample. This is because this is rather easy to read and conceptualize for a visual based graph. In our proper statistics we'll use different transformations (i.e. center log transformation).

Link

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Citations

Phyloseq:

phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data. Paul J. McMurdie and Susan Holmes (2013) PLoS ONE 8(4):e61217.

ggplot:

H. Wickham. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2016.

Speedyseq:

McLaren M (2023). speedyseq: Faster implementations of phyloseq functions. https://mikemc.github.io/speedyseq, https://github.com/mikemc/speedyseq.