The goal of corebiota is to provide a set of functions to easily and robustly perform core microbiota analysis from an ASV/OTU table. It also put emphasis on robustness by providing a probabilistic framework and reproducibility.
The API is as follow:
-
First, with the function
sad
you can rapidly perform a species abundance distribution modeling following a Poisson distribution and identify microbes belonging to either core or satellite group in your community. -
You can also directly get the core microbiota through
get_core
.
Miscellaneous functions, nonetheless important, are:
plot_graph
function which plot a nice graph showin the partition of you microbiome into satellite and core members.get_satellite
which return the satellite members of your community.
Yes, all the function can take as input a phyloseq object.
This package have only phyloseq as an external dependcy for your joy. We therefore, extensively use R Base and only pheatmap, covr and usethis as suggests.
You can install the development version of corebiota like so:
# Install devtools package (if not already done!)
install.package("remotes")
# Load devtools package
library(remotes)
# Install corebiota package
install_github("Ebedthan/corebiota")
This is a basic example which shows you how to solve a common problem:
library(corebiota)
# Some fake data
asv_tbl <- data.frame(sample1 = 1:10, sample2 = 10:1, sample3 = 80:89)
rownames(asv_tbl) <- paste0("ASV", "_", 1:10)
sad(asv_tbl)
Enjoy!
- Neu, A.T., Allen, E.E., Roy, K., 2021. Defining and quantifying the core microbiome: Challenges and prospects. PNAS 118. https://doi.org/10.1073/pnas.2104429118
- Berg, G., Rybakova, D., Fischer, D. et al., 2020. Microbiome definition re-visited: old concepts and new challenges. Microbiome 8, 103. https://doi.org/10.1186/s40168-020-00875-0
- Astudillo‐García, C., Bell, J.J., Webster, N.S. et al., 2017. Evaluating the core microbiota in complex communities: A systematic investigation. Environ Microbiol 19, 1450–1462. https://doi.org/10.1111/1462-2920.13647