R packages

These are the R libraries that you will need to install to analyze data output from the hecatomb workflow. Some are installable directly, and other optional libraries will require BioConductor that we will also install.

Recommended libraries:

These are libraries we have found essential for working with hecatomb data.

To install the recommended libraries, the command below can be entered directly into an R console, preferably accessed using Rstudio, or optionally using R from the command line:

install.packages(c("BiocManager", "tidyverse",  "tidylog", "rstatix"), dependencies = TRUE)

• BiocManager: Allows access to Bioconductor Project packages
• tidyverse: A standard to work with data in a tidy way in R. Includes ggplot, dplyr and more
• tidylog: Provides additional details about your tidy operations in the RStudio console (optional but highly recommended)
• rstatix: tidy statistics in R (also technically optional, but used extensively for statistical analysis of hecatomb data in our lab)

Optional libraries:

These are libraries that we have found to be useful for analyzing data output by the hecatomb workflow:

• data.table: A high-performance version of base R's data.frame. Really useful for fast, memory efficient operations, particularly for large data tables. If you are struggling with slow i/o performance or other table operations such as joins then consider using data.table
• phyloseq: Hecatomb's data format is largely based on Phyloseq. As such, many of the built in functions of phyloseq may be applicable to your analysis.
• plotly: An interface to the brilliant interactive plotly library from the plots you create from ggplot. Useful if you want to use your mouse to select specific parts of a plot for visualization.