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Probabilistic partition of count data to identify core species

Home Page: https://ebedthan.github.io/corebiota

License: GNU General Public License v3.0

R 100.00%
bioinformatics microbiome r

corebiota's Introduction

corebiota

R-CMD-check Codecov test coverage License: GPL v3 Codacy Badge

Probabilistic core microbiota analysis

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.

Installation

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")

Example

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!

Some great papers on designing a core microbiota analysis

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