https://github.com/ebedthan/corebiota
Probabilistic partition of count data to identify core species
https://github.com/ebedthan/corebiota
bioinformatics microbiome r
Last synced: 3 months ago
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Probabilistic partition of count data to identify core species
- Host: GitHub
- URL: https://github.com/ebedthan/corebiota
- Owner: Ebedthan
- License: gpl-3.0
- Created: 2022-01-04T09:38:54.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2023-04-27T16:31:38.000Z (about 2 years ago)
- Last Synced: 2025-01-22T18:51:25.731Z (5 months ago)
- Topics: bioinformatics, microbiome, r
- Language: R
- Homepage: https://ebedthan.github.io/corebiota
- Size: 2.63 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
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README
# corebiota 
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## 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`](https://ebedthan.github.io/corebiota/reference/sad.html) 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`](https://ebedthan.github.io/corebiota/reference/get_core.html).
Miscellaneous functions, nonetheless important, are:
- [`plot_graph`](https://ebedthan.github.io/corebiota/reference/plot_graph.html) function which plot a nice graph showin the partition of you microbiome into satellite and core members.
- [`get_satellite`](https://ebedthan.github.io/corebiota/reference/get_satellite.html) 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:
``` r
# 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:
``` r
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
- Neu, A.T., Allen, E.E., Roy, K., 2021. Defining and quantifying the core microbiome: Challenges and prospects. PNAS 118.
- Berg, G., Rybakova, D., Fischer, D. et al., 2020. Microbiome definition re-visited: old concepts and new challenges. Microbiome 8, 103.
- 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.